End of training
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.gitignore
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checkpoint-*/
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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- wer
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model-index:
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- name: openai/whisper-small
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# openai/whisper-small
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.9569
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- Cer: 304.7818
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- Wer: 369.68
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 4
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 64
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 1000
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- training_steps: 50
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### Training results
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### Framework versions
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- Transformers 4.28.0.dev0
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- Pytorch 2.0.0+cu117
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- Datasets 2.10.2.dev0
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- Tokenizers 0.13.2
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added_tokens.json
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}
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all_results.json
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{
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"epoch": 1.31,
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"eval_cer": 304.78184991274,
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"eval_loss": 1.9569354057312012,
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"eval_runtime": 28.0459,
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"eval_samples_per_second": 1.783,
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"eval_steps_per_second": 0.071,
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"eval_wer": 369.68,
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"train_loss": 2.721541290283203,
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"train_runtime": 665.7853,
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"train_samples_per_second": 4.806,
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"train_steps_per_second": 0.075
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}
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best_model/added_tokens.json
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43 |
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"<|ka|>": 50329,
|
44 |
+
"<|kk|>": 50316,
|
45 |
+
"<|km|>": 50323,
|
46 |
+
"<|kn|>": 50306,
|
47 |
+
"<|ko|>": 50264,
|
48 |
+
"<|la|>": 50294,
|
49 |
+
"<|lb|>": 50345,
|
50 |
+
"<|ln|>": 50353,
|
51 |
+
"<|lo|>": 50336,
|
52 |
+
"<|lt|>": 50293,
|
53 |
+
"<|lv|>": 50301,
|
54 |
+
"<|mg|>": 50349,
|
55 |
+
"<|mi|>": 50295,
|
56 |
+
"<|mk|>": 50308,
|
57 |
+
"<|ml|>": 50296,
|
58 |
+
"<|mn|>": 50314,
|
59 |
+
"<|mr|>": 50320,
|
60 |
+
"<|ms|>": 50282,
|
61 |
+
"<|mt|>": 50343,
|
62 |
+
"<|my|>": 50346,
|
63 |
+
"<|ne|>": 50313,
|
64 |
+
"<|nl|>": 50271,
|
65 |
+
"<|nn|>": 50342,
|
66 |
+
"<|nocaptions|>": 50362,
|
67 |
+
"<|notimestamps|>": 50363,
|
68 |
+
"<|no|>": 50288,
|
69 |
+
"<|oc|>": 50328,
|
70 |
+
"<|pa|>": 50321,
|
71 |
+
"<|pl|>": 50269,
|
72 |
+
"<|ps|>": 50340,
|
73 |
+
"<|pt|>": 50267,
|
74 |
+
"<|ro|>": 50284,
|
75 |
+
"<|ru|>": 50263,
|
76 |
+
"<|sa|>": 50344,
|
77 |
+
"<|sd|>": 50332,
|
78 |
+
"<|si|>": 50322,
|
79 |
+
"<|sk|>": 50298,
|
80 |
+
"<|sl|>": 50305,
|
81 |
+
"<|sn|>": 50324,
|
82 |
+
"<|so|>": 50326,
|
83 |
+
"<|sq|>": 50317,
|
84 |
+
"<|sr|>": 50303,
|
85 |
+
"<|startoflm|>": 50360,
|
86 |
+
"<|startofprev|>": 50361,
|
87 |
+
"<|startoftranscript|>": 50258,
|
88 |
+
"<|su|>": 50357,
|
89 |
+
"<|sv|>": 50273,
|
90 |
+
"<|sw|>": 50318,
|
91 |
+
"<|ta|>": 50287,
|
92 |
+
"<|te|>": 50299,
|
93 |
+
"<|tg|>": 50331,
|
94 |
+
"<|th|>": 50289,
|
95 |
+
"<|tk|>": 50341,
|
96 |
+
"<|tl|>": 50348,
|
97 |
+
"<|transcribe|>": 50359,
|
98 |
+
"<|translate|>": 50358,
|
99 |
+
"<|tr|>": 50268,
|
100 |
+
"<|tt|>": 50351,
|
101 |
+
"<|uk|>": 50280,
|
102 |
+
"<|ur|>": 50290,
|
103 |
+
"<|uz|>": 50337,
|
104 |
+
"<|vi|>": 50278,
|
105 |
+
"<|yi|>": 50335,
|
106 |
+
"<|yo|>": 50325,
|
107 |
+
"<|zh|>": 50260
|
108 |
+
}
|
best_model/merges.txt
ADDED
The diff for this file is too large to render.
See raw diff
|
|
best_model/normalizer.json
ADDED
@@ -0,0 +1,1742 @@
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|
1 |
+
{
|
2 |
+
"accessorise": "accessorize",
|
3 |
+
"accessorised": "accessorized",
|
4 |
+
"accessorises": "accessorizes",
|
5 |
+
"accessorising": "accessorizing",
|
6 |
+
"acclimatisation": "acclimatization",
|
7 |
+
"acclimatise": "acclimatize",
|
8 |
+
"acclimatised": "acclimatized",
|
9 |
+
"acclimatises": "acclimatizes",
|
10 |
+
"acclimatising": "acclimatizing",
|
11 |
+
"accoutrements": "accouterments",
|
12 |
+
"aeon": "eon",
|
13 |
+
"aeons": "eons",
|
14 |
+
"aerogramme": "aerogram",
|
15 |
+
"aerogrammes": "aerograms",
|
16 |
+
"aeroplane": "airplane",
|
17 |
+
"aeroplanes": "airplanes",
|
18 |
+
"aesthete": "esthete",
|
19 |
+
"aesthetes": "esthetes",
|
20 |
+
"aesthetic": "esthetic",
|
21 |
+
"aesthetically": "esthetically",
|
22 |
+
"aesthetics": "esthetics",
|
23 |
+
"aetiology": "etiology",
|
24 |
+
"ageing": "aging",
|
25 |
+
"aggrandisement": "aggrandizement",
|
26 |
+
"agonise": "agonize",
|
27 |
+
"agonised": "agonized",
|
28 |
+
"agonises": "agonizes",
|
29 |
+
"agonising": "agonizing",
|
30 |
+
"agonisingly": "agonizingly",
|
31 |
+
"almanack": "almanac",
|
32 |
+
"almanacks": "almanacs",
|
33 |
+
"aluminium": "aluminum",
|
34 |
+
"amortisable": "amortizable",
|
35 |
+
"amortisation": "amortization",
|
36 |
+
"amortisations": "amortizations",
|
37 |
+
"amortise": "amortize",
|
38 |
+
"amortised": "amortized",
|
39 |
+
"amortises": "amortizes",
|
40 |
+
"amortising": "amortizing",
|
41 |
+
"amphitheatre": "amphitheater",
|
42 |
+
"amphitheatres": "amphitheaters",
|
43 |
+
"anaemia": "anemia",
|
44 |
+
"anaemic": "anemic",
|
45 |
+
"anaesthesia": "anesthesia",
|
46 |
+
"anaesthetic": "anesthetic",
|
47 |
+
"anaesthetics": "anesthetics",
|
48 |
+
"anaesthetise": "anesthetize",
|
49 |
+
"anaesthetised": "anesthetized",
|
50 |
+
"anaesthetises": "anesthetizes",
|
51 |
+
"anaesthetising": "anesthetizing",
|
52 |
+
"anaesthetist": "anesthetist",
|
53 |
+
"anaesthetists": "anesthetists",
|
54 |
+
"anaesthetize": "anesthetize",
|
55 |
+
"anaesthetized": "anesthetized",
|
56 |
+
"anaesthetizes": "anesthetizes",
|
57 |
+
"anaesthetizing": "anesthetizing",
|
58 |
+
"analogue": "analog",
|
59 |
+
"analogues": "analogs",
|
60 |
+
"analyse": "analyze",
|
61 |
+
"analysed": "analyzed",
|
62 |
+
"analyses": "analyzes",
|
63 |
+
"analysing": "analyzing",
|
64 |
+
"anglicise": "anglicize",
|
65 |
+
"anglicised": "anglicized",
|
66 |
+
"anglicises": "anglicizes",
|
67 |
+
"anglicising": "anglicizing",
|
68 |
+
"annualised": "annualized",
|
69 |
+
"antagonise": "antagonize",
|
70 |
+
"antagonised": "antagonized",
|
71 |
+
"antagonises": "antagonizes",
|
72 |
+
"antagonising": "antagonizing",
|
73 |
+
"apologise": "apologize",
|
74 |
+
"apologised": "apologized",
|
75 |
+
"apologises": "apologizes",
|
76 |
+
"apologising": "apologizing",
|
77 |
+
"appal": "appall",
|
78 |
+
"appals": "appalls",
|
79 |
+
"appetiser": "appetizer",
|
80 |
+
"appetisers": "appetizers",
|
81 |
+
"appetising": "appetizing",
|
82 |
+
"appetisingly": "appetizingly",
|
83 |
+
"arbour": "arbor",
|
84 |
+
"arbours": "arbors",
|
85 |
+
"archaeologically": "archeologically",
|
86 |
+
"archaeologist": "archeologist",
|
87 |
+
"archaeologists": "archeologists",
|
88 |
+
"archaeology": "archeology</span>",
|
89 |
+
"archeological": "archaeological",
|
90 |
+
"ardour": "ardor",
|
91 |
+
"armour": "armor",
|
92 |
+
"armoured": "armored",
|
93 |
+
"armourer": "armorer",
|
94 |
+
"armourers": "armorers",
|
95 |
+
"armouries": "armories",
|
96 |
+
"armoury": "armory",
|
97 |
+
"artefact": "artifact",
|
98 |
+
"artefacts": "artifacts",
|
99 |
+
"authorise": "authorize",
|
100 |
+
"authorised": "authorized",
|
101 |
+
"authorises": "authorizes",
|
102 |
+
"authorising": "authorizing",
|
103 |
+
"axe": "ax",
|
104 |
+
"backpedalled": "backpedaled",
|
105 |
+
"backpedalling": "backpedaling",
|
106 |
+
"bannister": "banister",
|
107 |
+
"bannisters": "banisters",
|
108 |
+
"baptise": "baptize",
|
109 |
+
"baptised": "baptized",
|
110 |
+
"baptises": "baptizes",
|
111 |
+
"baptising": "baptizing",
|
112 |
+
"bastardise": "bastardize",
|
113 |
+
"bastardised": "bastardized",
|
114 |
+
"bastardises": "bastardizes",
|
115 |
+
"bastardising": "bastardizing",
|
116 |
+
"battleax": "battleaxe",
|
117 |
+
"baulk": "balk",
|
118 |
+
"baulked": "balked",
|
119 |
+
"baulking": "balking",
|
120 |
+
"baulks": "balks",
|
121 |
+
"bedevilled": "bedeviled",
|
122 |
+
"bedevilling": "bedeviling",
|
123 |
+
"behaviour": "behavior",
|
124 |
+
"behavioural": "behavioral",
|
125 |
+
"behaviourism": "behaviorism",
|
126 |
+
"behaviourist": "behaviorist",
|
127 |
+
"behaviourists": "behaviorists",
|
128 |
+
"behaviours": "behaviors",
|
129 |
+
"behove": "behoove",
|
130 |
+
"behoved": "behooved",
|
131 |
+
"behoves": "behooves",
|
132 |
+
"bejewelled": "bejeweled",
|
133 |
+
"belabour": "belabor",
|
134 |
+
"belaboured": "belabored",
|
135 |
+
"belabouring": "belaboring",
|
136 |
+
"belabours": "belabors",
|
137 |
+
"bevelled": "beveled",
|
138 |
+
"bevvies": "bevies",
|
139 |
+
"bevvy": "bevy",
|
140 |
+
"biassed": "biased",
|
141 |
+
"biassing": "biasing",
|
142 |
+
"bingeing": "binging",
|
143 |
+
"bougainvillaea": "bougainvillea",
|
144 |
+
"bougainvillaeas": "bougainvilleas",
|
145 |
+
"bowdlerise": "bowdlerize",
|
146 |
+
"bowdlerised": "bowdlerized",
|
147 |
+
"bowdlerises": "bowdlerizes",
|
148 |
+
"bowdlerising": "bowdlerizing",
|
149 |
+
"breathalyse": "breathalyze",
|
150 |
+
"breathalysed": "breathalyzed",
|
151 |
+
"breathalyser": "breathalyzer",
|
152 |
+
"breathalysers": "breathalyzers",
|
153 |
+
"breathalyses": "breathalyzes",
|
154 |
+
"breathalysing": "breathalyzing",
|
155 |
+
"brutalise": "brutalize",
|
156 |
+
"brutalised": "brutalized",
|
157 |
+
"brutalises": "brutalizes",
|
158 |
+
"brutalising": "brutalizing",
|
159 |
+
"busses": "buses",
|
160 |
+
"bussing": "busing",
|
161 |
+
"caesarean": "cesarean",
|
162 |
+
"caesareans": "cesareans",
|
163 |
+
"calibre": "caliber",
|
164 |
+
"calibres": "calibers",
|
165 |
+
"calliper": "caliper",
|
166 |
+
"callipers": "calipers",
|
167 |
+
"callisthenics": "calisthenics",
|
168 |
+
"canalise": "canalize",
|
169 |
+
"canalised": "canalized",
|
170 |
+
"canalises": "canalizes",
|
171 |
+
"canalising": "canalizing",
|
172 |
+
"cancelation": "cancellation",
|
173 |
+
"cancelations": "cancellations",
|
174 |
+
"cancelled": "canceled",
|
175 |
+
"cancelling": "canceling",
|
176 |
+
"candour": "candor",
|
177 |
+
"cannibalise": "cannibalize",
|
178 |
+
"cannibalised": "cannibalized",
|
179 |
+
"cannibalises": "cannibalizes",
|
180 |
+
"cannibalising": "cannibalizing",
|
181 |
+
"canonise": "canonize",
|
182 |
+
"canonised": "canonized",
|
183 |
+
"canonises": "canonizes",
|
184 |
+
"canonising": "canonizing",
|
185 |
+
"capitalise": "capitalize",
|
186 |
+
"capitalised": "capitalized",
|
187 |
+
"capitalises": "capitalizes",
|
188 |
+
"capitalising": "capitalizing",
|
189 |
+
"caramelise": "caramelize",
|
190 |
+
"caramelised": "caramelized",
|
191 |
+
"caramelises": "caramelizes",
|
192 |
+
"caramelising": "caramelizing",
|
193 |
+
"carbonise": "carbonize",
|
194 |
+
"carbonised": "carbonized",
|
195 |
+
"carbonises": "carbonizes",
|
196 |
+
"carbonising": "carbonizing",
|
197 |
+
"carolled": "caroled",
|
198 |
+
"carolling": "caroling",
|
199 |
+
"catalogue": "catalog",
|
200 |
+
"catalogued": "cataloged",
|
201 |
+
"catalogues": "catalogs",
|
202 |
+
"cataloguing": "cataloging",
|
203 |
+
"catalyse": "catalyze",
|
204 |
+
"catalysed": "catalyzed",
|
205 |
+
"catalyses": "catalyzes",
|
206 |
+
"catalysing": "catalyzing",
|
207 |
+
"categorise": "categorize",
|
208 |
+
"categorised": "categorized",
|
209 |
+
"categorises": "categorizes",
|
210 |
+
"categorising": "categorizing",
|
211 |
+
"cauterise": "cauterize",
|
212 |
+
"cauterised": "cauterized",
|
213 |
+
"cauterises": "cauterizes",
|
214 |
+
"cauterising": "cauterizing",
|
215 |
+
"cavilled": "caviled",
|
216 |
+
"cavilling": "caviling",
|
217 |
+
"centigramme": "centigram",
|
218 |
+
"centigrammes": "centigrams",
|
219 |
+
"centilitre": "centiliter",
|
220 |
+
"centilitres": "centiliters",
|
221 |
+
"centimetre": "centimeter",
|
222 |
+
"centimetres": "centimeters",
|
223 |
+
"centralise": "centralize",
|
224 |
+
"centralised": "centralized",
|
225 |
+
"centralises": "centralizes",
|
226 |
+
"centralising": "centralizing",
|
227 |
+
"centre": "center",
|
228 |
+
"centred": "centered",
|
229 |
+
"centrefold": "centerfold",
|
230 |
+
"centrefolds": "centerfolds",
|
231 |
+
"centrepiece": "centerpiece",
|
232 |
+
"centrepieces": "centerpieces",
|
233 |
+
"centres": "centers",
|
234 |
+
"channelled": "channeled",
|
235 |
+
"channelling": "channeling",
|
236 |
+
"characterise": "characterize",
|
237 |
+
"characterised": "characterized",
|
238 |
+
"characterises": "characterizes",
|
239 |
+
"characterising": "characterizing",
|
240 |
+
"cheque": "check",
|
241 |
+
"chequebook": "checkbook",
|
242 |
+
"chequebooks": "checkbooks",
|
243 |
+
"chequered": "checkered",
|
244 |
+
"cheques": "checks",
|
245 |
+
"chilli": "chili",
|
246 |
+
"chimaera": "chimera",
|
247 |
+
"chimaeras": "chimeras",
|
248 |
+
"chiselled": "chiseled",
|
249 |
+
"chiselling": "chiseling",
|
250 |
+
"circularise": "circularize",
|
251 |
+
"circularised": "circularized",
|
252 |
+
"circularises": "circularizes",
|
253 |
+
"circularising": "circularizing",
|
254 |
+
"civilise": "civilize",
|
255 |
+
"civilised": "civilized",
|
256 |
+
"civilises": "civilizes",
|
257 |
+
"civilising": "civilizing",
|
258 |
+
"clamour": "clamor",
|
259 |
+
"clamoured": "clamored",
|
260 |
+
"clamouring": "clamoring",
|
261 |
+
"clamours": "clamors",
|
262 |
+
"clangour": "clangor",
|
263 |
+
"clarinettist": "clarinetist",
|
264 |
+
"clarinettists": "clarinetists",
|
265 |
+
"collectivise": "collectivize",
|
266 |
+
"collectivised": "collectivized",
|
267 |
+
"collectivises": "collectivizes",
|
268 |
+
"collectivising": "collectivizing",
|
269 |
+
"colonisation": "colonization",
|
270 |
+
"colonise": "colonize",
|
271 |
+
"colonised": "colonized",
|
272 |
+
"coloniser": "colonizer",
|
273 |
+
"colonisers": "colonizers",
|
274 |
+
"colonises": "colonizes",
|
275 |
+
"colonising": "colonizing",
|
276 |
+
"colour": "color",
|
277 |
+
"colourant": "colorant",
|
278 |
+
"colourants": "colorants",
|
279 |
+
"coloured": "colored",
|
280 |
+
"coloureds": "coloreds",
|
281 |
+
"colourful": "colorful",
|
282 |
+
"colourfully": "colorfully",
|
283 |
+
"colouring": "coloring",
|
284 |
+
"colourize": "colorize",
|
285 |
+
"colourized": "colorized",
|
286 |
+
"colourizes": "colorizes",
|
287 |
+
"colourizing": "colorizing",
|
288 |
+
"colourless": "colorless",
|
289 |
+
"colours": "colors",
|
290 |
+
"commercialise": "commercialize",
|
291 |
+
"commercialised": "commercialized",
|
292 |
+
"commercialises": "commercializes",
|
293 |
+
"commercialising": "commercializing",
|
294 |
+
"compartmentalise": "compartmentalize",
|
295 |
+
"compartmentalised": "compartmentalized",
|
296 |
+
"compartmentalises": "compartmentalizes",
|
297 |
+
"compartmentalising": "compartmentalizing",
|
298 |
+
"computerise": "computerize",
|
299 |
+
"computerised": "computerized",
|
300 |
+
"computerises": "computerizes",
|
301 |
+
"computerising": "computerizing",
|
302 |
+
"conceptualise": "conceptualize",
|
303 |
+
"conceptualised": "conceptualized",
|
304 |
+
"conceptualises": "conceptualizes",
|
305 |
+
"conceptualising": "conceptualizing",
|
306 |
+
"connexion": "connection",
|
307 |
+
"connexions": "connections",
|
308 |
+
"contextualise": "contextualize",
|
309 |
+
"contextualised": "contextualized",
|
310 |
+
"contextualises": "contextualizes",
|
311 |
+
"contextualising": "contextualizing",
|
312 |
+
"cosier": "cozier",
|
313 |
+
"cosies": "cozies",
|
314 |
+
"cosiest": "coziest",
|
315 |
+
"cosily": "cozily",
|
316 |
+
"cosiness": "coziness",
|
317 |
+
"cosy": "cozy",
|
318 |
+
"councillor": "councilor",
|
319 |
+
"councillors": "councilors",
|
320 |
+
"counselled": "counseled",
|
321 |
+
"counselling": "counseling",
|
322 |
+
"counsellor": "counselor",
|
323 |
+
"counsellors": "counselors",
|
324 |
+
"crenelated": "crenellated",
|
325 |
+
"criminalise": "criminalize",
|
326 |
+
"criminalised": "criminalized",
|
327 |
+
"criminalises": "criminalizes",
|
328 |
+
"criminalising": "criminalizing",
|
329 |
+
"criticise": "criticize",
|
330 |
+
"criticised": "criticized",
|
331 |
+
"criticises": "criticizes",
|
332 |
+
"criticising": "criticizing",
|
333 |
+
"crueller": "crueler",
|
334 |
+
"cruellest": "cruelest",
|
335 |
+
"crystallisation": "crystallization",
|
336 |
+
"crystallise": "crystallize",
|
337 |
+
"crystallised": "crystallized",
|
338 |
+
"crystallises": "crystallizes",
|
339 |
+
"crystallising": "crystallizing",
|
340 |
+
"cudgelled": "cudgeled",
|
341 |
+
"cudgelling": "cudgeling",
|
342 |
+
"customise": "customize",
|
343 |
+
"customised": "customized",
|
344 |
+
"customises": "customizes",
|
345 |
+
"customising": "customizing",
|
346 |
+
"cypher": "cipher",
|
347 |
+
"cyphers": "ciphers",
|
348 |
+
"decentralisation": "decentralization",
|
349 |
+
"decentralise": "decentralize",
|
350 |
+
"decentralised": "decentralized",
|
351 |
+
"decentralises": "decentralizes",
|
352 |
+
"decentralising": "decentralizing",
|
353 |
+
"decriminalisation": "decriminalization",
|
354 |
+
"decriminalise": "decriminalize",
|
355 |
+
"decriminalised": "decriminalized",
|
356 |
+
"decriminalises": "decriminalizes",
|
357 |
+
"decriminalising": "decriminalizing",
|
358 |
+
"defence": "defense",
|
359 |
+
"defenceless": "defenseless",
|
360 |
+
"defences": "defenses",
|
361 |
+
"dehumanisation": "dehumanization",
|
362 |
+
"dehumanise": "dehumanize",
|
363 |
+
"dehumanised": "dehumanized",
|
364 |
+
"dehumanises": "dehumanizes",
|
365 |
+
"dehumanising": "dehumanizing",
|
366 |
+
"demeanour": "demeanor",
|
367 |
+
"demilitarisation": "demilitarization",
|
368 |
+
"demilitarise": "demilitarize",
|
369 |
+
"demilitarised": "demilitarized",
|
370 |
+
"demilitarises": "demilitarizes",
|
371 |
+
"demilitarising": "demilitarizing",
|
372 |
+
"demobilisation": "demobilization",
|
373 |
+
"demobilise": "demobilize",
|
374 |
+
"demobilised": "demobilized",
|
375 |
+
"demobilises": "demobilizes",
|
376 |
+
"demobilising": "demobilizing",
|
377 |
+
"democratisation": "democratization",
|
378 |
+
"democratise": "democratize",
|
379 |
+
"democratised": "democratized",
|
380 |
+
"democratises": "democratizes",
|
381 |
+
"democratising": "democratizing",
|
382 |
+
"demonise": "demonize",
|
383 |
+
"demonised": "demonized",
|
384 |
+
"demonises": "demonizes",
|
385 |
+
"demonising": "demonizing",
|
386 |
+
"demoralisation": "demoralization",
|
387 |
+
"demoralise": "demoralize",
|
388 |
+
"demoralised": "demoralized",
|
389 |
+
"demoralises": "demoralizes",
|
390 |
+
"demoralising": "demoralizing",
|
391 |
+
"denationalisation": "denationalization",
|
392 |
+
"denationalise": "denationalize",
|
393 |
+
"denationalised": "denationalized",
|
394 |
+
"denationalises": "denationalizes",
|
395 |
+
"denationalising": "denationalizing",
|
396 |
+
"deodorise": "deodorize",
|
397 |
+
"deodorised": "deodorized",
|
398 |
+
"deodorises": "deodorizes",
|
399 |
+
"deodorising": "deodorizing",
|
400 |
+
"depersonalise": "depersonalize",
|
401 |
+
"depersonalised": "depersonalized",
|
402 |
+
"depersonalises": "depersonalizes",
|
403 |
+
"depersonalising": "depersonalizing",
|
404 |
+
"deputise": "deputize",
|
405 |
+
"deputised": "deputized",
|
406 |
+
"deputises": "deputizes",
|
407 |
+
"deputising": "deputizing",
|
408 |
+
"desensitisation": "desensitization",
|
409 |
+
"desensitise": "desensitize",
|
410 |
+
"desensitised": "desensitized",
|
411 |
+
"desensitises": "desensitizes",
|
412 |
+
"desensitising": "desensitizing",
|
413 |
+
"destabilisation": "destabilization",
|
414 |
+
"destabilise": "destabilize",
|
415 |
+
"destabilised": "destabilized",
|
416 |
+
"destabilises": "destabilizes",
|
417 |
+
"destabilising": "destabilizing",
|
418 |
+
"dialled": "dialed",
|
419 |
+
"dialling": "dialing",
|
420 |
+
"dialogue": "dialog",
|
421 |
+
"dialogues": "dialogs",
|
422 |
+
"diarrhoea": "diarrhea",
|
423 |
+
"digitise": "digitize",
|
424 |
+
"digitised": "digitized",
|
425 |
+
"digitises": "digitizes",
|
426 |
+
"digitising": "digitizing",
|
427 |
+
"disc": "disk",
|
428 |
+
"discolour": "discolor",
|
429 |
+
"discoloured": "discolored",
|
430 |
+
"discolouring": "discoloring",
|
431 |
+
"discolours": "discolors",
|
432 |
+
"discs": "disks",
|
433 |
+
"disembowelled": "disemboweled",
|
434 |
+
"disembowelling": "disemboweling",
|
435 |
+
"disfavour": "disfavor",
|
436 |
+
"dishevelled": "disheveled",
|
437 |
+
"dishonour": "dishonor",
|
438 |
+
"dishonourable": "dishonorable",
|
439 |
+
"dishonourably": "dishonorably",
|
440 |
+
"dishonoured": "dishonored",
|
441 |
+
"dishonouring": "dishonoring",
|
442 |
+
"dishonours": "dishonors",
|
443 |
+
"disorganisation": "disorganization",
|
444 |
+
"disorganised": "disorganized",
|
445 |
+
"distil": "distill",
|
446 |
+
"distils": "distills",
|
447 |
+
"dramatisation": "dramatization",
|
448 |
+
"dramatisations": "dramatizations",
|
449 |
+
"dramatise": "dramatize",
|
450 |
+
"dramatised": "dramatized",
|
451 |
+
"dramatises": "dramatizes",
|
452 |
+
"dramatising": "dramatizing",
|
453 |
+
"draught": "draft",
|
454 |
+
"draughtboard": "draftboard",
|
455 |
+
"draughtboards": "draftboards",
|
456 |
+
"draughtier": "draftier",
|
457 |
+
"draughtiest": "draftiest",
|
458 |
+
"draughts": "drafts",
|
459 |
+
"draughtsman": "draftsman",
|
460 |
+
"draughtsmanship": "draftsmanship",
|
461 |
+
"draughtsmen": "draftsmen",
|
462 |
+
"draughtswoman": "draftswoman",
|
463 |
+
"draughtswomen": "draftswomen",
|
464 |
+
"draughty": "drafty",
|
465 |
+
"drivelled": "driveled",
|
466 |
+
"drivelling": "driveling",
|
467 |
+
"duelled": "dueled",
|
468 |
+
"duelling": "dueling",
|
469 |
+
"economise": "economize",
|
470 |
+
"economised": "economized",
|
471 |
+
"economises": "economizes",
|
472 |
+
"economising": "economizing",
|
473 |
+
"editorialise": "editorialize",
|
474 |
+
"editorialised": "editorialized",
|
475 |
+
"editorialises": "editorializes",
|
476 |
+
"editorialising": "editorializing",
|
477 |
+
"edoema": "edema",
|
478 |
+
"empathise": "empathize",
|
479 |
+
"empathised": "empathized",
|
480 |
+
"empathises": "empathizes",
|
481 |
+
"empathising": "empathizing",
|
482 |
+
"emphasise": "emphasize",
|
483 |
+
"emphasised": "emphasized",
|
484 |
+
"emphasises": "emphasizes",
|
485 |
+
"emphasising": "emphasizing",
|
486 |
+
"enamelled": "enameled",
|
487 |
+
"enamelling": "enameling",
|
488 |
+
"enamoured": "enamored",
|
489 |
+
"encyclopaedia": "encyclopedia",
|
490 |
+
"encyclopaedias": "encyclopedias",
|
491 |
+
"encyclopaedic": "encyclopedic",
|
492 |
+
"endeavour": "endeavor",
|
493 |
+
"endeavoured": "endeavored",
|
494 |
+
"endeavouring": "endeavoring",
|
495 |
+
"endeavours": "endeavors",
|
496 |
+
"energise": "energize",
|
497 |
+
"energised": "energized",
|
498 |
+
"energises": "energizes",
|
499 |
+
"energising": "energizing",
|
500 |
+
"enrol": "enroll",
|
501 |
+
"enrols": "enrolls",
|
502 |
+
"enthral": "enthrall",
|
503 |
+
"enthrals": "enthralls",
|
504 |
+
"epaulette": "epaulet",
|
505 |
+
"epaulettes": "epaulets",
|
506 |
+
"epicentre": "epicenter",
|
507 |
+
"epicentres": "epicenters",
|
508 |
+
"epilogue": "epilog",
|
509 |
+
"epilogues": "epilogs",
|
510 |
+
"epitomise": "epitomize",
|
511 |
+
"epitomised": "epitomized",
|
512 |
+
"epitomises": "epitomizes",
|
513 |
+
"epitomising": "epitomizing",
|
514 |
+
"equalisation": "equalization",
|
515 |
+
"equalise": "equalize",
|
516 |
+
"equalised": "equalized",
|
517 |
+
"equaliser": "equalizer",
|
518 |
+
"equalisers": "equalizers",
|
519 |
+
"equalises": "equalizes",
|
520 |
+
"equalising": "equalizing",
|
521 |
+
"eulogise": "eulogize",
|
522 |
+
"eulogised": "eulogized",
|
523 |
+
"eulogises": "eulogizes",
|
524 |
+
"eulogising": "eulogizing",
|
525 |
+
"evangelise": "evangelize",
|
526 |
+
"evangelised": "evangelized",
|
527 |
+
"evangelises": "evangelizes",
|
528 |
+
"evangelising": "evangelizing",
|
529 |
+
"exorcise": "exorcize",
|
530 |
+
"exorcised": "exorcized",
|
531 |
+
"exorcises": "exorcizes",
|
532 |
+
"exorcising": "exorcizing",
|
533 |
+
"extemporisation": "extemporization",
|
534 |
+
"extemporise": "extemporize",
|
535 |
+
"extemporised": "extemporized",
|
536 |
+
"extemporises": "extemporizes",
|
537 |
+
"extemporising": "extemporizing",
|
538 |
+
"externalisation": "externalization",
|
539 |
+
"externalisations": "externalizations",
|
540 |
+
"externalise": "externalize",
|
541 |
+
"externalised": "externalized",
|
542 |
+
"externalises": "externalizes",
|
543 |
+
"externalising": "externalizing",
|
544 |
+
"factorise": "factorize",
|
545 |
+
"factorised": "factorized",
|
546 |
+
"factorises": "factorizes",
|
547 |
+
"factorising": "factorizing",
|
548 |
+
"faecal": "fecal",
|
549 |
+
"faeces": "feces",
|
550 |
+
"familiarisation": "familiarization",
|
551 |
+
"familiarise": "familiarize",
|
552 |
+
"familiarised": "familiarized",
|
553 |
+
"familiarises": "familiarizes",
|
554 |
+
"familiarising": "familiarizing",
|
555 |
+
"fantasise": "fantasize",
|
556 |
+
"fantasised": "fantasized",
|
557 |
+
"fantasises": "fantasizes",
|
558 |
+
"fantasising": "fantasizing",
|
559 |
+
"favour": "favor",
|
560 |
+
"favourable": "favorable",
|
561 |
+
"favourably": "favorably",
|
562 |
+
"favoured": "favored",
|
563 |
+
"favouring": "favoring",
|
564 |
+
"favourite": "favorite",
|
565 |
+
"favourites": "favorites",
|
566 |
+
"favouritism": "favoritism",
|
567 |
+
"favours": "favors",
|
568 |
+
"feminise": "feminize",
|
569 |
+
"feminised": "feminized",
|
570 |
+
"feminises": "feminizes",
|
571 |
+
"feminising": "feminizing",
|
572 |
+
"fertilisation": "fertilization",
|
573 |
+
"fertilise": "fertilize",
|
574 |
+
"fertilised": "fertilized",
|
575 |
+
"fertiliser": "fertilizer",
|
576 |
+
"fertilisers": "fertilizers",
|
577 |
+
"fertilises": "fertilizes",
|
578 |
+
"fertilising": "fertilizing",
|
579 |
+
"fervour": "fervor",
|
580 |
+
"fibre": "fiber",
|
581 |
+
"fibreglass": "fiberglass",
|
582 |
+
"fibres": "fibers",
|
583 |
+
"fictionalisation": "fictionalization",
|
584 |
+
"fictionalisations": "fictionalizations",
|
585 |
+
"fictionalise": "fictionalize",
|
586 |
+
"fictionalised": "fictionalized",
|
587 |
+
"fictionalises": "fictionalizes",
|
588 |
+
"fictionalising": "fictionalizing",
|
589 |
+
"fillet": "filet",
|
590 |
+
"filleted": "fileted",
|
591 |
+
"filleting": "fileting",
|
592 |
+
"fillets": "filets",
|
593 |
+
"finalisation": "finalization",
|
594 |
+
"finalise": "finalize",
|
595 |
+
"finalised": "finalized",
|
596 |
+
"finalises": "finalizes",
|
597 |
+
"finalising": "finalizing",
|
598 |
+
"flautist": "flutist",
|
599 |
+
"flautists": "flutists",
|
600 |
+
"flavour": "flavor",
|
601 |
+
"flavoured": "flavored",
|
602 |
+
"flavouring": "flavoring",
|
603 |
+
"flavourings": "flavorings",
|
604 |
+
"flavourless": "flavorless",
|
605 |
+
"flavours": "flavors",
|
606 |
+
"flavoursome": "flavorsome",
|
607 |
+
"flyer / flier": "flier / flyer",
|
608 |
+
"foetal": "fetal",
|
609 |
+
"foetid": "fetid",
|
610 |
+
"foetus": "fetus",
|
611 |
+
"foetuses": "fetuses",
|
612 |
+
"formalisation": "formalization",
|
613 |
+
"formalise": "formalize",
|
614 |
+
"formalised": "formalized",
|
615 |
+
"formalises": "formalizes",
|
616 |
+
"formalising": "formalizing",
|
617 |
+
"fossilisation": "fossilization",
|
618 |
+
"fossilise": "fossilize",
|
619 |
+
"fossilised": "fossilized",
|
620 |
+
"fossilises": "fossilizes",
|
621 |
+
"fossilising": "fossilizing",
|
622 |
+
"fraternisation": "fraternization",
|
623 |
+
"fraternise": "fraternize",
|
624 |
+
"fraternised": "fraternized",
|
625 |
+
"fraternises": "fraternizes",
|
626 |
+
"fraternising": "fraternizing",
|
627 |
+
"fulfil": "fulfill",
|
628 |
+
"fulfilment": "fulfillment",
|
629 |
+
"fulfils": "fulfills",
|
630 |
+
"funnelled": "funneled",
|
631 |
+
"funnelling": "funneling",
|
632 |
+
"gage": "gauge",
|
633 |
+
"gaged": "gauged",
|
634 |
+
"gages": "gauges",
|
635 |
+
"gaging": "gauging",
|
636 |
+
"galvanise": "galvanize",
|
637 |
+
"galvanised": "galvanized",
|
638 |
+
"galvanises": "galvanizes",
|
639 |
+
"galvanising": "galvanizing",
|
640 |
+
"gambolled": "gamboled",
|
641 |
+
"gambolling": "gamboling",
|
642 |
+
"gaol": "jail",
|
643 |
+
"gaolbird": "jailbird",
|
644 |
+
"gaolbirds": "jailbirds",
|
645 |
+
"gaolbreak": "jailbreak",
|
646 |
+
"gaolbreaks": "jailbreaks",
|
647 |
+
"gaoled": "jailed",
|
648 |
+
"gaoler": "jailer",
|
649 |
+
"gaolers": "jailers",
|
650 |
+
"gaoling": "jailing",
|
651 |
+
"gaols": "jails",
|
652 |
+
"gasses": "gases",
|
653 |
+
"generalisation": "generalization",
|
654 |
+
"generalisations": "generalizations",
|
655 |
+
"generalise": "generalize",
|
656 |
+
"generalised": "generalized",
|
657 |
+
"generalises": "generalizes",
|
658 |
+
"generalising": "generalizing",
|
659 |
+
"ghettoise": "ghettoize",
|
660 |
+
"ghettoised": "ghettoized",
|
661 |
+
"ghettoises": "ghettoizes",
|
662 |
+
"ghettoising": "ghettoizing",
|
663 |
+
"gipsies": "gypsies",
|
664 |
+
"glamor": "glamour",
|
665 |
+
"glamorise": "glamorize",
|
666 |
+
"glamorised": "glamorized",
|
667 |
+
"glamorises": "glamorizes",
|
668 |
+
"glamorising": "glamorizing",
|
669 |
+
"globalisation": "globalization",
|
670 |
+
"globalise": "globalize",
|
671 |
+
"globalised": "globalized",
|
672 |
+
"globalises": "globalizes",
|
673 |
+
"globalising": "globalizing",
|
674 |
+
"glueing": "gluing",
|
675 |
+
"goitre": "goiter",
|
676 |
+
"goitres": "goiters",
|
677 |
+
"gonorrhoea": "gonorrhea",
|
678 |
+
"gramme": "gram",
|
679 |
+
"grammes": "grams",
|
680 |
+
"gravelled": "graveled",
|
681 |
+
"grey": "gray",
|
682 |
+
"greyed": "grayed",
|
683 |
+
"greying": "graying",
|
684 |
+
"greyish": "grayish",
|
685 |
+
"greyness": "grayness",
|
686 |
+
"greys": "grays",
|
687 |
+
"grovelled": "groveled",
|
688 |
+
"grovelling": "groveling",
|
689 |
+
"groyne": "groin",
|
690 |
+
"groynes": "groins",
|
691 |
+
"gruelling": "grueling",
|
692 |
+
"gruellingly": "gruelingly",
|
693 |
+
"gryphon": "griffin",
|
694 |
+
"gryphons": "griffins",
|
695 |
+
"gynaecological": "gynecological",
|
696 |
+
"gynaecologist": "gynecologist",
|
697 |
+
"gynaecologists": "gynecologists",
|
698 |
+
"gynaecology": "gynecology",
|
699 |
+
"haematological": "hematological",
|
700 |
+
"haematologist": "hematologist",
|
701 |
+
"haematologists": "hematologists",
|
702 |
+
"haematology": "hematology",
|
703 |
+
"haemoglobin": "hemoglobin",
|
704 |
+
"haemophilia": "hemophilia",
|
705 |
+
"haemophiliac": "hemophiliac",
|
706 |
+
"haemophiliacs": "hemophiliacs",
|
707 |
+
"haemorrhage": "hemorrhage",
|
708 |
+
"haemorrhaged": "hemorrhaged",
|
709 |
+
"haemorrhages": "hemorrhages",
|
710 |
+
"haemorrhaging": "hemorrhaging",
|
711 |
+
"haemorrhoids": "hemorrhoids",
|
712 |
+
"harbour": "harbor",
|
713 |
+
"harboured": "harbored",
|
714 |
+
"harbouring": "harboring",
|
715 |
+
"harbours": "harbors",
|
716 |
+
"harmonisation": "harmonization",
|
717 |
+
"harmonise": "harmonize",
|
718 |
+
"harmonised": "harmonized",
|
719 |
+
"harmonises": "harmonizes",
|
720 |
+
"harmonising": "harmonizing",
|
721 |
+
"homoeopath": "homeopath",
|
722 |
+
"homoeopathic": "homeopathic",
|
723 |
+
"homoeopaths": "homeopaths",
|
724 |
+
"homoeopathy": "homeopathy",
|
725 |
+
"homogenise": "homogenize",
|
726 |
+
"homogenised": "homogenized",
|
727 |
+
"homogenises": "homogenizes",
|
728 |
+
"homogenising": "homogenizing",
|
729 |
+
"honour": "honor",
|
730 |
+
"honourable": "honorable",
|
731 |
+
"honourably": "honorably",
|
732 |
+
"honoured": "honored",
|
733 |
+
"honouring": "honoring",
|
734 |
+
"honours": "honors",
|
735 |
+
"hospitalisation": "hospitalization",
|
736 |
+
"hospitalise": "hospitalize",
|
737 |
+
"hospitalised": "hospitalized",
|
738 |
+
"hospitalises": "hospitalizes",
|
739 |
+
"hospitalising": "hospitalizing",
|
740 |
+
"humanise": "humanize",
|
741 |
+
"humanised": "humanized",
|
742 |
+
"humanises": "humanizes",
|
743 |
+
"humanising": "humanizing",
|
744 |
+
"humour": "humor",
|
745 |
+
"humoured": "humored",
|
746 |
+
"humouring": "humoring",
|
747 |
+
"humourless": "humorless",
|
748 |
+
"humours": "humors",
|
749 |
+
"hybridise": "hybridize",
|
750 |
+
"hybridised": "hybridized",
|
751 |
+
"hybridises": "hybridizes",
|
752 |
+
"hybridising": "hybridizing",
|
753 |
+
"hypnotise": "hypnotize",
|
754 |
+
"hypnotised": "hypnotized",
|
755 |
+
"hypnotises": "hypnotizes",
|
756 |
+
"hypnotising": "hypnotizing",
|
757 |
+
"hypothesise": "hypothesize",
|
758 |
+
"hypothesised": "hypothesized",
|
759 |
+
"hypothesises": "hypothesizes",
|
760 |
+
"hypothesising": "hypothesizing",
|
761 |
+
"idealisation": "idealization",
|
762 |
+
"idealise": "idealize",
|
763 |
+
"idealised": "idealized",
|
764 |
+
"idealises": "idealizes",
|
765 |
+
"idealising": "idealizing",
|
766 |
+
"idolise": "idolize",
|
767 |
+
"idolised": "idolized",
|
768 |
+
"idolises": "idolizes",
|
769 |
+
"idolising": "idolizing",
|
770 |
+
"immobilisation": "immobilization",
|
771 |
+
"immobilise": "immobilize",
|
772 |
+
"immobilised": "immobilized",
|
773 |
+
"immobiliser": "immobilizer",
|
774 |
+
"immobilisers": "immobilizers",
|
775 |
+
"immobilises": "immobilizes",
|
776 |
+
"immobilising": "immobilizing",
|
777 |
+
"immortalise": "immortalize",
|
778 |
+
"immortalised": "immortalized",
|
779 |
+
"immortalises": "immortalizes",
|
780 |
+
"immortalising": "immortalizing",
|
781 |
+
"immunisation": "immunization",
|
782 |
+
"immunise": "immunize",
|
783 |
+
"immunised": "immunized",
|
784 |
+
"immunises": "immunizes",
|
785 |
+
"immunising": "immunizing",
|
786 |
+
"impanelled": "impaneled",
|
787 |
+
"impanelling": "impaneling",
|
788 |
+
"imperilled": "imperiled",
|
789 |
+
"imperilling": "imperiling",
|
790 |
+
"individualise": "individualize",
|
791 |
+
"individualised": "individualized",
|
792 |
+
"individualises": "individualizes",
|
793 |
+
"individualising": "individualizing",
|
794 |
+
"industrialise": "industrialize",
|
795 |
+
"industrialised": "industrialized",
|
796 |
+
"industrialises": "industrializes",
|
797 |
+
"industrialising": "industrializing",
|
798 |
+
"inflexion": "inflection",
|
799 |
+
"inflexions": "inflections",
|
800 |
+
"initialise": "initialize",
|
801 |
+
"initialised": "initialized",
|
802 |
+
"initialises": "initializes",
|
803 |
+
"initialising": "initializing",
|
804 |
+
"initialled": "initialed",
|
805 |
+
"initialling": "initialing",
|
806 |
+
"instal": "install",
|
807 |
+
"instalment": "installment",
|
808 |
+
"instalments": "installments",
|
809 |
+
"instals": "installs",
|
810 |
+
"instil": "instill",
|
811 |
+
"instils": "instills",
|
812 |
+
"institutionalisation": "institutionalization",
|
813 |
+
"institutionalise": "institutionalize",
|
814 |
+
"institutionalised": "institutionalized",
|
815 |
+
"institutionalises": "institutionalizes",
|
816 |
+
"institutionalising": "institutionalizing",
|
817 |
+
"intellectualise": "intellectualize",
|
818 |
+
"intellectualised": "intellectualized",
|
819 |
+
"intellectualises": "intellectualizes",
|
820 |
+
"intellectualising": "intellectualizing",
|
821 |
+
"internalisation": "internalization",
|
822 |
+
"internalise": "internalize",
|
823 |
+
"internalised": "internalized",
|
824 |
+
"internalises": "internalizes",
|
825 |
+
"internalising": "internalizing",
|
826 |
+
"internationalisation": "internationalization",
|
827 |
+
"internationalise": "internationalize",
|
828 |
+
"internationalised": "internationalized",
|
829 |
+
"internationalises": "internationalizes",
|
830 |
+
"internationalising": "internationalizing",
|
831 |
+
"ionisation": "ionization",
|
832 |
+
"ionise": "ionize",
|
833 |
+
"ionised": "ionized",
|
834 |
+
"ioniser": "ionizer",
|
835 |
+
"ionisers": "ionizers",
|
836 |
+
"ionises": "ionizes",
|
837 |
+
"ionising": "ionizing",
|
838 |
+
"italicise": "italicize",
|
839 |
+
"italicised": "italicized",
|
840 |
+
"italicises": "italicizes",
|
841 |
+
"italicising": "italicizing",
|
842 |
+
"itemise": "itemize",
|
843 |
+
"itemised": "itemized",
|
844 |
+
"itemises": "itemizes",
|
845 |
+
"itemising": "itemizing",
|
846 |
+
"jeopardise": "jeopardize",
|
847 |
+
"jeopardised": "jeopardized",
|
848 |
+
"jeopardises": "jeopardizes",
|
849 |
+
"jeopardising": "jeopardizing",
|
850 |
+
"jewelled": "jeweled",
|
851 |
+
"jeweller": "jeweler",
|
852 |
+
"jewellers": "jewelers",
|
853 |
+
"jewellery": "jewelry",
|
854 |
+
"judgement": "judgment",
|
855 |
+
"kilogramme": "kilogram",
|
856 |
+
"kilogrammes": "kilograms",
|
857 |
+
"kilometre": "kilometer",
|
858 |
+
"kilometres": "kilometers",
|
859 |
+
"labelled": "labeled",
|
860 |
+
"labelling": "labeling",
|
861 |
+
"labour": "labor",
|
862 |
+
"laboured": "labored",
|
863 |
+
"labourer": "laborer",
|
864 |
+
"labourers": "laborers",
|
865 |
+
"labouring": "laboring",
|
866 |
+
"labours": "labors",
|
867 |
+
"lacklustre": "lackluster",
|
868 |
+
"legalisation": "legalization",
|
869 |
+
"legalise": "legalize",
|
870 |
+
"legalised": "legalized",
|
871 |
+
"legalises": "legalizes",
|
872 |
+
"legalising": "legalizing",
|
873 |
+
"legitimise": "legitimize",
|
874 |
+
"legitimised": "legitimized",
|
875 |
+
"legitimises": "legitimizes",
|
876 |
+
"legitimising": "legitimizing",
|
877 |
+
"leukaemia": "leukemia",
|
878 |
+
"levelled": "leveled",
|
879 |
+
"leveller": "leveler",
|
880 |
+
"levellers": "levelers",
|
881 |
+
"levelling": "leveling",
|
882 |
+
"libelled": "libeled",
|
883 |
+
"libelling": "libeling",
|
884 |
+
"libellous": "libelous",
|
885 |
+
"liberalisation": "liberalization",
|
886 |
+
"liberalise": "liberalize",
|
887 |
+
"liberalised": "liberalized",
|
888 |
+
"liberalises": "liberalizes",
|
889 |
+
"liberalising": "liberalizing",
|
890 |
+
"licence": "license",
|
891 |
+
"licenced": "licensed",
|
892 |
+
"licences": "licenses",
|
893 |
+
"licencing": "licensing",
|
894 |
+
"likeable": "likable",
|
895 |
+
"lionisation": "lionization",
|
896 |
+
"lionise": "lionize",
|
897 |
+
"lionised": "lionized",
|
898 |
+
"lionises": "lionizes",
|
899 |
+
"lionising": "lionizing",
|
900 |
+
"liquidise": "liquidize",
|
901 |
+
"liquidised": "liquidized",
|
902 |
+
"liquidiser": "liquidizer",
|
903 |
+
"liquidisers": "liquidizers",
|
904 |
+
"liquidises": "liquidizes",
|
905 |
+
"liquidising": "liquidizing",
|
906 |
+
"litre": "liter",
|
907 |
+
"litres": "liters",
|
908 |
+
"localise": "localize",
|
909 |
+
"localised": "localized",
|
910 |
+
"localises": "localizes",
|
911 |
+
"localising": "localizing",
|
912 |
+
"louvre": "louver",
|
913 |
+
"louvred": "louvered",
|
914 |
+
"louvres": "louvers",
|
915 |
+
"lustre": "luster",
|
916 |
+
"magnetise": "magnetize",
|
917 |
+
"magnetised": "magnetized",
|
918 |
+
"magnetises": "magnetizes",
|
919 |
+
"magnetising": "magnetizing",
|
920 |
+
"manoeuvrability": "maneuverability",
|
921 |
+
"manoeuvrable": "maneuverable",
|
922 |
+
"manoeuvre": "maneuver",
|
923 |
+
"manoeuvred": "maneuvered",
|
924 |
+
"manoeuvres": "maneuvers",
|
925 |
+
"manoeuvring": "maneuvering",
|
926 |
+
"manoeuvrings": "maneuverings",
|
927 |
+
"marginalisation": "marginalization",
|
928 |
+
"marginalise": "marginalize",
|
929 |
+
"marginalised": "marginalized",
|
930 |
+
"marginalises": "marginalizes",
|
931 |
+
"marginalising": "marginalizing",
|
932 |
+
"marshalled": "marshaled",
|
933 |
+
"marshalling": "marshaling",
|
934 |
+
"marvelled": "marveled",
|
935 |
+
"marvelling": "marveling",
|
936 |
+
"marvellous": "marvelous",
|
937 |
+
"marvellously": "marvelously",
|
938 |
+
"materialisation": "materialization",
|
939 |
+
"materialise": "materialize",
|
940 |
+
"materialised": "materialized",
|
941 |
+
"materialises": "materializes",
|
942 |
+
"materialising": "materializing",
|
943 |
+
"maximisation": "maximization",
|
944 |
+
"maximise": "maximize",
|
945 |
+
"maximised": "maximized",
|
946 |
+
"maximises": "maximizes",
|
947 |
+
"maximising": "maximizing",
|
948 |
+
"meagre": "meager",
|
949 |
+
"mechanisation": "mechanization",
|
950 |
+
"mechanise": "mechanize",
|
951 |
+
"mechanised": "mechanized",
|
952 |
+
"mechanises": "mechanizes",
|
953 |
+
"mechanising": "mechanizing",
|
954 |
+
"mediaeval": "medieval",
|
955 |
+
"memorialise": "memorialize",
|
956 |
+
"memorialised": "memorialized",
|
957 |
+
"memorialises": "memorializes",
|
958 |
+
"memorialising": "memorializing",
|
959 |
+
"memorise": "memorize",
|
960 |
+
"memorised": "memorized",
|
961 |
+
"memorises": "memorizes",
|
962 |
+
"memorising": "memorizing",
|
963 |
+
"mesmerise": "mesmerize",
|
964 |
+
"mesmerised": "mesmerized",
|
965 |
+
"mesmerises": "mesmerizes",
|
966 |
+
"mesmerising": "mesmerizing",
|
967 |
+
"metabolise": "metabolize",
|
968 |
+
"metabolised": "metabolized",
|
969 |
+
"metabolises": "metabolizes",
|
970 |
+
"metabolising": "metabolizing",
|
971 |
+
"metre": "meter",
|
972 |
+
"metres": "meters",
|
973 |
+
"mhm": "hmm",
|
974 |
+
"micrometre": "micrometer",
|
975 |
+
"micrometres": "micrometers",
|
976 |
+
"militarise": "militarize",
|
977 |
+
"militarised": "militarized",
|
978 |
+
"militarises": "militarizes",
|
979 |
+
"militarising": "militarizing",
|
980 |
+
"milligramme": "milligram",
|
981 |
+
"milligrammes": "milligrams",
|
982 |
+
"millilitre": "milliliter",
|
983 |
+
"millilitres": "milliliters",
|
984 |
+
"millimetre": "millimeter",
|
985 |
+
"millimetres": "millimeters",
|
986 |
+
"miniaturisation": "miniaturization",
|
987 |
+
"miniaturise": "miniaturize",
|
988 |
+
"miniaturised": "miniaturized",
|
989 |
+
"miniaturises": "miniaturizes",
|
990 |
+
"miniaturising": "miniaturizing",
|
991 |
+
"minibusses": "minibuses",
|
992 |
+
"minimise": "minimize",
|
993 |
+
"minimised": "minimized",
|
994 |
+
"minimises": "minimizes",
|
995 |
+
"minimising": "minimizing",
|
996 |
+
"misbehaviour": "misbehavior",
|
997 |
+
"misdemeanour": "misdemeanor",
|
998 |
+
"misdemeanours": "misdemeanors",
|
999 |
+
"misspelt": "misspelled",
|
1000 |
+
"mitre": "miter",
|
1001 |
+
"mitres": "miters",
|
1002 |
+
"mm": "hmm",
|
1003 |
+
"mmm": "hmm",
|
1004 |
+
"mobilisation": "mobilization",
|
1005 |
+
"mobilise": "mobilize",
|
1006 |
+
"mobilised": "mobilized",
|
1007 |
+
"mobilises": "mobilizes",
|
1008 |
+
"mobilising": "mobilizing",
|
1009 |
+
"modelled": "modeled",
|
1010 |
+
"modeller": "modeler",
|
1011 |
+
"modellers": "modelers",
|
1012 |
+
"modelling": "modeling",
|
1013 |
+
"modernise": "modernize",
|
1014 |
+
"modernised": "modernized",
|
1015 |
+
"modernises": "modernizes",
|
1016 |
+
"modernising": "modernizing",
|
1017 |
+
"moisturise": "moisturize",
|
1018 |
+
"moisturised": "moisturized",
|
1019 |
+
"moisturiser": "moisturizer",
|
1020 |
+
"moisturisers": "moisturizers",
|
1021 |
+
"moisturises": "moisturizes",
|
1022 |
+
"moisturising": "moisturizing",
|
1023 |
+
"monologue": "monolog",
|
1024 |
+
"monologues": "monologs",
|
1025 |
+
"monopolisation": "monopolization",
|
1026 |
+
"monopolise": "monopolize",
|
1027 |
+
"monopolised": "monopolized",
|
1028 |
+
"monopolises": "monopolizes",
|
1029 |
+
"monopolising": "monopolizing",
|
1030 |
+
"moralise": "moralize",
|
1031 |
+
"moralised": "moralized",
|
1032 |
+
"moralises": "moralizes",
|
1033 |
+
"moralising": "moralizing",
|
1034 |
+
"motorised": "motorized",
|
1035 |
+
"mould": "mold",
|
1036 |
+
"moulded": "molded",
|
1037 |
+
"moulder": "molder",
|
1038 |
+
"mouldered": "moldered",
|
1039 |
+
"mouldering": "moldering",
|
1040 |
+
"moulders": "molders",
|
1041 |
+
"mouldier": "moldier",
|
1042 |
+
"mouldiest": "moldiest",
|
1043 |
+
"moulding": "molding",
|
1044 |
+
"mouldings": "moldings",
|
1045 |
+
"moulds": "molds",
|
1046 |
+
"mouldy": "moldy",
|
1047 |
+
"moult": "molt",
|
1048 |
+
"moulted": "molted",
|
1049 |
+
"moulting": "molting",
|
1050 |
+
"moults": "molts",
|
1051 |
+
"moustache": "mustache",
|
1052 |
+
"moustached": "mustached",
|
1053 |
+
"moustaches": "mustaches",
|
1054 |
+
"moustachioed": "mustachioed",
|
1055 |
+
"multicoloured": "multicolored",
|
1056 |
+
"nationalisation": "nationalization",
|
1057 |
+
"nationalisations": "nationalizations",
|
1058 |
+
"nationalise": "nationalize",
|
1059 |
+
"nationalised": "nationalized",
|
1060 |
+
"nationalises": "nationalizes",
|
1061 |
+
"nationalising": "nationalizing",
|
1062 |
+
"naturalisation": "naturalization",
|
1063 |
+
"naturalise": "naturalize",
|
1064 |
+
"naturalised": "naturalized",
|
1065 |
+
"naturalises": "naturalizes",
|
1066 |
+
"naturalising": "naturalizing",
|
1067 |
+
"neighbour": "neighbor",
|
1068 |
+
"neighbourhood": "neighborhood",
|
1069 |
+
"neighbourhoods": "neighborhoods",
|
1070 |
+
"neighbouring": "neighboring",
|
1071 |
+
"neighbourliness": "neighborliness",
|
1072 |
+
"neighbourly": "neighborly",
|
1073 |
+
"neighbours": "neighbors",
|
1074 |
+
"neutralisation": "neutralization",
|
1075 |
+
"neutralise": "neutralize",
|
1076 |
+
"neutralised": "neutralized",
|
1077 |
+
"neutralises": "neutralizes",
|
1078 |
+
"neutralising": "neutralizing",
|
1079 |
+
"normalisation": "normalization",
|
1080 |
+
"normalise": "normalize",
|
1081 |
+
"normalised": "normalized",
|
1082 |
+
"normalises": "normalizes",
|
1083 |
+
"normalising": "normalizing",
|
1084 |
+
"odour": "odor",
|
1085 |
+
"odourless": "odorless",
|
1086 |
+
"odours": "odors",
|
1087 |
+
"oesophagus": "esophagus",
|
1088 |
+
"oesophaguses": "esophaguses",
|
1089 |
+
"oestrogen": "estrogen",
|
1090 |
+
"offence": "offense",
|
1091 |
+
"offences": "offenses",
|
1092 |
+
"omelette": "omelet",
|
1093 |
+
"omelettes": "omelets",
|
1094 |
+
"optimise": "optimize",
|
1095 |
+
"optimised": "optimized",
|
1096 |
+
"optimises": "optimizes",
|
1097 |
+
"optimising": "optimizing",
|
1098 |
+
"organisation": "organization",
|
1099 |
+
"organisational": "organizational",
|
1100 |
+
"organisations": "organizations",
|
1101 |
+
"organise": "organize",
|
1102 |
+
"organised": "organized",
|
1103 |
+
"organiser": "organizer",
|
1104 |
+
"organisers": "organizers",
|
1105 |
+
"organises": "organizes",
|
1106 |
+
"organising": "organizing",
|
1107 |
+
"orthopaedic": "orthopedic",
|
1108 |
+
"orthopaedics": "orthopedics",
|
1109 |
+
"ostracise": "ostracize",
|
1110 |
+
"ostracised": "ostracized",
|
1111 |
+
"ostracises": "ostracizes",
|
1112 |
+
"ostracising": "ostracizing",
|
1113 |
+
"outmanoeuvre": "outmaneuver",
|
1114 |
+
"outmanoeuvred": "outmaneuvered",
|
1115 |
+
"outmanoeuvres": "outmaneuvers",
|
1116 |
+
"outmanoeuvring": "outmaneuvering",
|
1117 |
+
"overemphasise": "overemphasize",
|
1118 |
+
"overemphasised": "overemphasized",
|
1119 |
+
"overemphasises": "overemphasizes",
|
1120 |
+
"overemphasising": "overemphasizing",
|
1121 |
+
"oxidisation": "oxidization",
|
1122 |
+
"oxidise": "oxidize",
|
1123 |
+
"oxidised": "oxidized",
|
1124 |
+
"oxidises": "oxidizes",
|
1125 |
+
"oxidising": "oxidizing",
|
1126 |
+
"paederast": "pederast",
|
1127 |
+
"paederasts": "pederasts",
|
1128 |
+
"paediatric": "pediatric",
|
1129 |
+
"paediatrician": "pediatrician",
|
1130 |
+
"paediatricians": "pediatricians",
|
1131 |
+
"paediatrics": "pediatrics",
|
1132 |
+
"paedophile": "pedophile",
|
1133 |
+
"paedophiles": "pedophiles",
|
1134 |
+
"paedophilia": "pedophilia",
|
1135 |
+
"palaeolithic": "paleolithic",
|
1136 |
+
"palaeontologist": "paleontologist",
|
1137 |
+
"palaeontologists": "paleontologists",
|
1138 |
+
"palaeontology": "paleontology",
|
1139 |
+
"panelled": "paneled",
|
1140 |
+
"panelling": "paneling",
|
1141 |
+
"panellist": "panelist",
|
1142 |
+
"panellists": "panelists",
|
1143 |
+
"paralyse": "paralyze",
|
1144 |
+
"paralysed": "paralyzed",
|
1145 |
+
"paralyses": "paralyzes",
|
1146 |
+
"paralysing": "paralyzing",
|
1147 |
+
"parcelled": "parceled",
|
1148 |
+
"parcelling": "parceling",
|
1149 |
+
"parlour": "parlor",
|
1150 |
+
"parlours": "parlors",
|
1151 |
+
"particularise": "particularize",
|
1152 |
+
"particularised": "particularized",
|
1153 |
+
"particularises": "particularizes",
|
1154 |
+
"particularising": "particularizing",
|
1155 |
+
"passivisation": "passivization",
|
1156 |
+
"passivise": "passivize",
|
1157 |
+
"passivised": "passivized",
|
1158 |
+
"passivises": "passivizes",
|
1159 |
+
"passivising": "passivizing",
|
1160 |
+
"pasteurisation": "pasteurization",
|
1161 |
+
"pasteurise": "pasteurize",
|
1162 |
+
"pasteurised": "pasteurized",
|
1163 |
+
"pasteurises": "pasteurizes",
|
1164 |
+
"pasteurising": "pasteurizing",
|
1165 |
+
"patronise": "patronize",
|
1166 |
+
"patronised": "patronized",
|
1167 |
+
"patronises": "patronizes",
|
1168 |
+
"patronising": "patronizing",
|
1169 |
+
"patronisingly": "patronizingly",
|
1170 |
+
"pedalled": "pedaled",
|
1171 |
+
"pedalling": "pedaling",
|
1172 |
+
"pedestrianisation": "pedestrianization",
|
1173 |
+
"pedestrianise": "pedestrianize",
|
1174 |
+
"pedestrianised": "pedestrianized",
|
1175 |
+
"pedestrianises": "pedestrianizes",
|
1176 |
+
"pedestrianising": "pedestrianizing",
|
1177 |
+
"penalise": "penalize",
|
1178 |
+
"penalised": "penalized",
|
1179 |
+
"penalises": "penalizes",
|
1180 |
+
"penalising": "penalizing",
|
1181 |
+
"pencilled": "penciled",
|
1182 |
+
"pencilling": "penciling",
|
1183 |
+
"personalise": "personalize",
|
1184 |
+
"personalised": "personalized",
|
1185 |
+
"personalises": "personalizes",
|
1186 |
+
"personalising": "personalizing",
|
1187 |
+
"pharmacopoeia": "pharmacopeia",
|
1188 |
+
"pharmacopoeias": "pharmacopeias",
|
1189 |
+
"philosophise": "philosophize",
|
1190 |
+
"philosophised": "philosophized",
|
1191 |
+
"philosophises": "philosophizes",
|
1192 |
+
"philosophising": "philosophizing",
|
1193 |
+
"philtre": "filter",
|
1194 |
+
"philtres": "filters",
|
1195 |
+
"phoney": "phony",
|
1196 |
+
"plagiarise": "plagiarize",
|
1197 |
+
"plagiarised": "plagiarized",
|
1198 |
+
"plagiarises": "plagiarizes",
|
1199 |
+
"plagiarising": "plagiarizing",
|
1200 |
+
"plough": "plow",
|
1201 |
+
"ploughed": "plowed",
|
1202 |
+
"ploughing": "plowing",
|
1203 |
+
"ploughman": "plowman",
|
1204 |
+
"ploughmen": "plowmen",
|
1205 |
+
"ploughs": "plows",
|
1206 |
+
"ploughshare": "plowshare",
|
1207 |
+
"ploughshares": "plowshares",
|
1208 |
+
"polarisation": "polarization",
|
1209 |
+
"polarise": "polarize",
|
1210 |
+
"polarised": "polarized",
|
1211 |
+
"polarises": "polarizes",
|
1212 |
+
"polarising": "polarizing",
|
1213 |
+
"politicisation": "politicization",
|
1214 |
+
"politicise": "politicize",
|
1215 |
+
"politicised": "politicized",
|
1216 |
+
"politicises": "politicizes",
|
1217 |
+
"politicising": "politicizing",
|
1218 |
+
"popularisation": "popularization",
|
1219 |
+
"popularise": "popularize",
|
1220 |
+
"popularised": "popularized",
|
1221 |
+
"popularises": "popularizes",
|
1222 |
+
"popularising": "popularizing",
|
1223 |
+
"pouffe": "pouf",
|
1224 |
+
"pouffes": "poufs",
|
1225 |
+
"practise": "practice",
|
1226 |
+
"practised": "practiced",
|
1227 |
+
"practises": "practices",
|
1228 |
+
"practising": "practicing",
|
1229 |
+
"praesidium": "presidium",
|
1230 |
+
"praesidiums": "presidiums",
|
1231 |
+
"pressurisation": "pressurization",
|
1232 |
+
"pressurise": "pressurize",
|
1233 |
+
"pressurised": "pressurized",
|
1234 |
+
"pressurises": "pressurizes",
|
1235 |
+
"pressurising": "pressurizing",
|
1236 |
+
"pretence": "pretense",
|
1237 |
+
"pretences": "pretenses",
|
1238 |
+
"primaeval": "primeval",
|
1239 |
+
"prioritisation": "prioritization",
|
1240 |
+
"prioritise": "prioritize",
|
1241 |
+
"prioritised": "prioritized",
|
1242 |
+
"prioritises": "prioritizes",
|
1243 |
+
"prioritising": "prioritizing",
|
1244 |
+
"privatisation": "privatization",
|
1245 |
+
"privatisations": "privatizations",
|
1246 |
+
"privatise": "privatize",
|
1247 |
+
"privatised": "privatized",
|
1248 |
+
"privatises": "privatizes",
|
1249 |
+
"privatising": "privatizing",
|
1250 |
+
"professionalisation": "professionalization",
|
1251 |
+
"professionalise": "professionalize",
|
1252 |
+
"professionalised": "professionalized",
|
1253 |
+
"professionalises": "professionalizes",
|
1254 |
+
"professionalising": "professionalizing",
|
1255 |
+
"programme": "program",
|
1256 |
+
"programmes": "programs",
|
1257 |
+
"prologue": "prolog",
|
1258 |
+
"prologues": "prologs",
|
1259 |
+
"propagandise": "propagandize",
|
1260 |
+
"propagandised": "propagandized",
|
1261 |
+
"propagandises": "propagandizes",
|
1262 |
+
"propagandising": "propagandizing",
|
1263 |
+
"proselytise": "proselytize",
|
1264 |
+
"proselytised": "proselytized",
|
1265 |
+
"proselytiser": "proselytizer",
|
1266 |
+
"proselytisers": "proselytizers",
|
1267 |
+
"proselytises": "proselytizes",
|
1268 |
+
"proselytising": "proselytizing",
|
1269 |
+
"psychoanalyse": "psychoanalyze",
|
1270 |
+
"psychoanalysed": "psychoanalyzed",
|
1271 |
+
"psychoanalyses": "psychoanalyzes",
|
1272 |
+
"psychoanalysing": "psychoanalyzing",
|
1273 |
+
"publicise": "publicize",
|
1274 |
+
"publicised": "publicized",
|
1275 |
+
"publicises": "publicizes",
|
1276 |
+
"publicising": "publicizing",
|
1277 |
+
"pulverisation": "pulverization",
|
1278 |
+
"pulverise": "pulverize",
|
1279 |
+
"pulverised": "pulverized",
|
1280 |
+
"pulverises": "pulverizes",
|
1281 |
+
"pulverising": "pulverizing",
|
1282 |
+
"pummelled": "pummel",
|
1283 |
+
"pummelling": "pummeled",
|
1284 |
+
"pyjama": "pajama",
|
1285 |
+
"pyjamas": "pajamas",
|
1286 |
+
"pzazz": "pizzazz",
|
1287 |
+
"quarrelled": "quarreled",
|
1288 |
+
"quarrelling": "quarreling",
|
1289 |
+
"radicalise": "radicalize",
|
1290 |
+
"radicalised": "radicalized",
|
1291 |
+
"radicalises": "radicalizes",
|
1292 |
+
"radicalising": "radicalizing",
|
1293 |
+
"rancour": "rancor",
|
1294 |
+
"randomise": "randomize",
|
1295 |
+
"randomised": "randomized",
|
1296 |
+
"randomises": "randomizes",
|
1297 |
+
"randomising": "randomizing",
|
1298 |
+
"rationalisation": "rationalization",
|
1299 |
+
"rationalisations": "rationalizations",
|
1300 |
+
"rationalise": "rationalize",
|
1301 |
+
"rationalised": "rationalized",
|
1302 |
+
"rationalises": "rationalizes",
|
1303 |
+
"rationalising": "rationalizing",
|
1304 |
+
"ravelled": "raveled",
|
1305 |
+
"ravelling": "raveling",
|
1306 |
+
"realisable": "realizable",
|
1307 |
+
"realisation": "realization",
|
1308 |
+
"realisations": "realizations",
|
1309 |
+
"realise": "realize",
|
1310 |
+
"realised": "realized",
|
1311 |
+
"realises": "realizes",
|
1312 |
+
"realising": "realizing",
|
1313 |
+
"recognisable": "recognizable",
|
1314 |
+
"recognisably": "recognizably",
|
1315 |
+
"recognisance": "recognizance",
|
1316 |
+
"recognise": "recognize",
|
1317 |
+
"recognised": "recognized",
|
1318 |
+
"recognises": "recognizes",
|
1319 |
+
"recognising": "recognizing",
|
1320 |
+
"reconnoitre": "reconnoiter",
|
1321 |
+
"reconnoitred": "reconnoitered",
|
1322 |
+
"reconnoitres": "reconnoiters",
|
1323 |
+
"reconnoitring": "reconnoitering",
|
1324 |
+
"refuelled": "refueled",
|
1325 |
+
"refuelling": "refueling",
|
1326 |
+
"regularisation": "regularization",
|
1327 |
+
"regularise": "regularize",
|
1328 |
+
"regularised": "regularized",
|
1329 |
+
"regularises": "regularizes",
|
1330 |
+
"regularising": "regularizing",
|
1331 |
+
"remodelled": "remodeled",
|
1332 |
+
"remodelling": "remodeling",
|
1333 |
+
"remould": "remold",
|
1334 |
+
"remoulded": "remolded",
|
1335 |
+
"remoulding": "remolding",
|
1336 |
+
"remoulds": "remolds",
|
1337 |
+
"reorganisation": "reorganization",
|
1338 |
+
"reorganisations": "reorganizations",
|
1339 |
+
"reorganise": "reorganize",
|
1340 |
+
"reorganised": "reorganized",
|
1341 |
+
"reorganises": "reorganizes",
|
1342 |
+
"reorganising": "reorganizing",
|
1343 |
+
"revelled": "reveled",
|
1344 |
+
"reveller": "reveler",
|
1345 |
+
"revellers": "revelers",
|
1346 |
+
"revelling": "reveling",
|
1347 |
+
"revitalise": "revitalize",
|
1348 |
+
"revitalised": "revitalized",
|
1349 |
+
"revitalises": "revitalizes",
|
1350 |
+
"revitalising": "revitalizing",
|
1351 |
+
"revolutionise": "revolutionize",
|
1352 |
+
"revolutionised": "revolutionized",
|
1353 |
+
"revolutionises": "revolutionizes",
|
1354 |
+
"revolutionising": "revolutionizing",
|
1355 |
+
"rhapsodise": "rhapsodize",
|
1356 |
+
"rhapsodised": "rhapsodized",
|
1357 |
+
"rhapsodises": "rhapsodizes",
|
1358 |
+
"rhapsodising": "rhapsodizing",
|
1359 |
+
"rigour": "rigor",
|
1360 |
+
"rigours": "rigors",
|
1361 |
+
"ritualised": "ritualized",
|
1362 |
+
"rivalled": "rivaled",
|
1363 |
+
"rivalling": "rivaling",
|
1364 |
+
"romanticise": "romanticize",
|
1365 |
+
"romanticised": "romanticized",
|
1366 |
+
"romanticises": "romanticizes",
|
1367 |
+
"romanticising": "romanticizing",
|
1368 |
+
"rumour": "rumor",
|
1369 |
+
"rumoured": "rumored",
|
1370 |
+
"rumours": "rumors",
|
1371 |
+
"sabre": "saber",
|
1372 |
+
"sabres": "sabers",
|
1373 |
+
"saltpetre": "saltpeter",
|
1374 |
+
"sanitise": "sanitize",
|
1375 |
+
"sanitised": "sanitized",
|
1376 |
+
"sanitises": "sanitizes",
|
1377 |
+
"sanitising": "sanitizing",
|
1378 |
+
"satirise": "satirize",
|
1379 |
+
"satirised": "satirized",
|
1380 |
+
"satirises": "satirizes",
|
1381 |
+
"satirising": "satirizing",
|
1382 |
+
"saviour": "savior",
|
1383 |
+
"saviours": "saviors",
|
1384 |
+
"savour": "savor",
|
1385 |
+
"savoured": "savored",
|
1386 |
+
"savouries": "savories",
|
1387 |
+
"savouring": "savoring",
|
1388 |
+
"savours": "savors",
|
1389 |
+
"savoury": "savory",
|
1390 |
+
"scandalise": "scandalize",
|
1391 |
+
"scandalised": "scandalized",
|
1392 |
+
"scandalises": "scandalizes",
|
1393 |
+
"scandalising": "scandalizing",
|
1394 |
+
"sceptic": "skeptic",
|
1395 |
+
"sceptical": "skeptical",
|
1396 |
+
"sceptically": "skeptically",
|
1397 |
+
"scepticism": "skepticism",
|
1398 |
+
"sceptics": "skeptics",
|
1399 |
+
"sceptre": "scepter",
|
1400 |
+
"sceptres": "scepters",
|
1401 |
+
"scrutinise": "scrutinize",
|
1402 |
+
"scrutinised": "scrutinized",
|
1403 |
+
"scrutinises": "scrutinizes",
|
1404 |
+
"scrutinising": "scrutinizing",
|
1405 |
+
"secularisation": "secularization",
|
1406 |
+
"secularise": "secularize",
|
1407 |
+
"secularised": "secularized",
|
1408 |
+
"secularises": "secularizes",
|
1409 |
+
"secularising": "secularizing",
|
1410 |
+
"sensationalise": "sensationalize",
|
1411 |
+
"sensationalised": "sensationalized",
|
1412 |
+
"sensationalises": "sensationalizes",
|
1413 |
+
"sensationalising": "sensationalizing",
|
1414 |
+
"sensitise": "sensitize",
|
1415 |
+
"sensitised": "sensitized",
|
1416 |
+
"sensitises": "sensitizes",
|
1417 |
+
"sensitising": "sensitizing",
|
1418 |
+
"sentimentalise": "sentimentalize",
|
1419 |
+
"sentimentalised": "sentimentalized",
|
1420 |
+
"sentimentalises": "sentimentalizes",
|
1421 |
+
"sentimentalising": "sentimentalizing",
|
1422 |
+
"sepulchre": "sepulcher",
|
1423 |
+
"sepulchres": "sepulchers",
|
1424 |
+
"serialisation": "serialization",
|
1425 |
+
"serialisations": "serializations",
|
1426 |
+
"serialise": "serialize",
|
1427 |
+
"serialised": "serialized",
|
1428 |
+
"serialises": "serializes",
|
1429 |
+
"serialising": "serializing",
|
1430 |
+
"sermonise": "sermonize",
|
1431 |
+
"sermonised": "sermonized",
|
1432 |
+
"sermonises": "sermonizes",
|
1433 |
+
"sermonising": "sermonizing",
|
1434 |
+
"sheikh": "sheik",
|
1435 |
+
"shovelled": "shoveled",
|
1436 |
+
"shovelling": "shoveling",
|
1437 |
+
"shrivelled": "shriveled",
|
1438 |
+
"shrivelling": "shriveling",
|
1439 |
+
"signalise": "signalize",
|
1440 |
+
"signalised": "signalized",
|
1441 |
+
"signalises": "signalizes",
|
1442 |
+
"signalising": "signalizing",
|
1443 |
+
"signalled": "signaled",
|
1444 |
+
"signalling": "signaling",
|
1445 |
+
"smoulder": "smolder",
|
1446 |
+
"smouldered": "smoldered",
|
1447 |
+
"smouldering": "smoldering",
|
1448 |
+
"smoulders": "smolders",
|
1449 |
+
"snivelled": "sniveled",
|
1450 |
+
"snivelling": "sniveling",
|
1451 |
+
"snorkelled": "snorkeled",
|
1452 |
+
"snorkelling": "snorkeling",
|
1453 |
+
"snowplough": "snowplow",
|
1454 |
+
"snowploughs": "snowplow",
|
1455 |
+
"socialisation": "socialization",
|
1456 |
+
"socialise": "socialize",
|
1457 |
+
"socialised": "socialized",
|
1458 |
+
"socialises": "socializes",
|
1459 |
+
"socialising": "socializing",
|
1460 |
+
"sodomise": "sodomize",
|
1461 |
+
"sodomised": "sodomized",
|
1462 |
+
"sodomises": "sodomizes",
|
1463 |
+
"sodomising": "sodomizing",
|
1464 |
+
"solemnise": "solemnize",
|
1465 |
+
"solemnised": "solemnized",
|
1466 |
+
"solemnises": "solemnizes",
|
1467 |
+
"solemnising": "solemnizing",
|
1468 |
+
"sombre": "somber",
|
1469 |
+
"specialisation": "specialization",
|
1470 |
+
"specialisations": "specializations",
|
1471 |
+
"specialise": "specialize",
|
1472 |
+
"specialised": "specialized",
|
1473 |
+
"specialises": "specializes",
|
1474 |
+
"specialising": "specializing",
|
1475 |
+
"spectre": "specter",
|
1476 |
+
"spectres": "specters",
|
1477 |
+
"spiralled": "spiraled",
|
1478 |
+
"spiralling": "spiraling",
|
1479 |
+
"splendour": "splendor",
|
1480 |
+
"splendours": "splendors",
|
1481 |
+
"squirrelled": "squirreled",
|
1482 |
+
"squirrelling": "squirreling",
|
1483 |
+
"stabilisation": "stabilization",
|
1484 |
+
"stabilise": "stabilize",
|
1485 |
+
"stabilised": "stabilized",
|
1486 |
+
"stabiliser": "stabilizer",
|
1487 |
+
"stabilisers": "stabilizers",
|
1488 |
+
"stabilises": "stabilizes",
|
1489 |
+
"stabilising": "stabilizing",
|
1490 |
+
"standardisation": "standardization",
|
1491 |
+
"standardise": "standardize",
|
1492 |
+
"standardised": "standardized",
|
1493 |
+
"standardises": "standardizes",
|
1494 |
+
"standardising": "standardizing",
|
1495 |
+
"stencilled": "stenciled",
|
1496 |
+
"stencilling": "stenciling",
|
1497 |
+
"sterilisation": "sterilization",
|
1498 |
+
"sterilisations": "sterilizations",
|
1499 |
+
"sterilise": "sterilize",
|
1500 |
+
"sterilised": "sterilized",
|
1501 |
+
"steriliser": "sterilizer",
|
1502 |
+
"sterilisers": "sterilizers",
|
1503 |
+
"sterilises": "sterilizes",
|
1504 |
+
"sterilising": "sterilizing",
|
1505 |
+
"stigmatisation": "stigmatization",
|
1506 |
+
"stigmatise": "stigmatize",
|
1507 |
+
"stigmatised": "stigmatized",
|
1508 |
+
"stigmatises": "stigmatizes",
|
1509 |
+
"stigmatising": "stigmatizing",
|
1510 |
+
"storey": "story",
|
1511 |
+
"storeys": "stories",
|
1512 |
+
"subsidisation": "subsidization",
|
1513 |
+
"subsidise": "subsidize",
|
1514 |
+
"subsidised": "subsidized",
|
1515 |
+
"subsidiser": "subsidizer",
|
1516 |
+
"subsidisers": "subsidizers",
|
1517 |
+
"subsidises": "subsidizes",
|
1518 |
+
"subsidising": "subsidizing",
|
1519 |
+
"succour": "succor",
|
1520 |
+
"succoured": "succored",
|
1521 |
+
"succouring": "succoring",
|
1522 |
+
"succours": "succors",
|
1523 |
+
"sulphate": "sulfate",
|
1524 |
+
"sulphates": "sulfates",
|
1525 |
+
"sulphide": "sulfide",
|
1526 |
+
"sulphides": "sulfides",
|
1527 |
+
"sulphur": "sulfur",
|
1528 |
+
"sulphurous": "sulfurous",
|
1529 |
+
"summarise": "summarize",
|
1530 |
+
"summarised": "summarized",
|
1531 |
+
"summarises": "summarizes",
|
1532 |
+
"summarising": "summarizing",
|
1533 |
+
"swivelled": "swiveled",
|
1534 |
+
"swivelling": "swiveling",
|
1535 |
+
"symbolise": "symbolize",
|
1536 |
+
"symbolised": "symbolized",
|
1537 |
+
"symbolises": "symbolizes",
|
1538 |
+
"symbolising": "symbolizing",
|
1539 |
+
"sympathise": "sympathize",
|
1540 |
+
"sympathised": "sympathized",
|
1541 |
+
"sympathiser": "sympathizer",
|
1542 |
+
"sympathisers": "sympathizers",
|
1543 |
+
"sympathises": "sympathizes",
|
1544 |
+
"sympathising": "sympathizing",
|
1545 |
+
"synchronisation": "synchronization",
|
1546 |
+
"synchronise": "synchronize",
|
1547 |
+
"synchronised": "synchronized",
|
1548 |
+
"synchronises": "synchronizes",
|
1549 |
+
"synchronising": "synchronizing",
|
1550 |
+
"synthesise": "synthesize",
|
1551 |
+
"synthesised": "synthesized",
|
1552 |
+
"synthesiser": "synthesizer",
|
1553 |
+
"synthesisers": "synthesizers",
|
1554 |
+
"synthesises": "synthesizes",
|
1555 |
+
"synthesising": "synthesizing",
|
1556 |
+
"syphon": "siphon",
|
1557 |
+
"syphoned": "siphoned",
|
1558 |
+
"syphoning": "siphoning",
|
1559 |
+
"syphons": "siphons",
|
1560 |
+
"systematisation": "systematization",
|
1561 |
+
"systematise": "systematize",
|
1562 |
+
"systematised": "systematized",
|
1563 |
+
"systematises": "systematizes",
|
1564 |
+
"systematising": "systematizing",
|
1565 |
+
"tantalise": "tantalize",
|
1566 |
+
"tantalised": "tantalized",
|
1567 |
+
"tantalises": "tantalizes",
|
1568 |
+
"tantalising": "tantalizing",
|
1569 |
+
"tantalisingly": "tantalizingly",
|
1570 |
+
"tasselled": "tasseled",
|
1571 |
+
"technicolour": "technicolor",
|
1572 |
+
"temporise": "temporize",
|
1573 |
+
"temporised": "temporized",
|
1574 |
+
"temporises": "temporizes",
|
1575 |
+
"temporising": "temporizing",
|
1576 |
+
"tenderise": "tenderize",
|
1577 |
+
"tenderised": "tenderized",
|
1578 |
+
"tenderises": "tenderizes",
|
1579 |
+
"tenderising": "tenderizing",
|
1580 |
+
"terrorise": "terrorize",
|
1581 |
+
"terrorised": "terrorized",
|
1582 |
+
"terrorises": "terrorizes",
|
1583 |
+
"terrorising": "terrorizing",
|
1584 |
+
"theatre": "theater",
|
1585 |
+
"theatregoer": "theatergoer",
|
1586 |
+
"theatregoers": "theatergoers",
|
1587 |
+
"theatres": "theaters",
|
1588 |
+
"theorise": "theorize",
|
1589 |
+
"theorised": "theorized",
|
1590 |
+
"theorises": "theorizes",
|
1591 |
+
"theorising": "theorizing",
|
1592 |
+
"tonne": "ton",
|
1593 |
+
"tonnes": "tons",
|
1594 |
+
"towelled": "toweled",
|
1595 |
+
"towelling": "toweling",
|
1596 |
+
"toxaemia": "toxemia",
|
1597 |
+
"tranquillise": "tranquilize",
|
1598 |
+
"tranquillised": "tranquilized",
|
1599 |
+
"tranquilliser": "tranquilizer",
|
1600 |
+
"tranquillisers": "tranquilizers",
|
1601 |
+
"tranquillises": "tranquilizes",
|
1602 |
+
"tranquillising": "tranquilizing",
|
1603 |
+
"tranquillity": "tranquility",
|
1604 |
+
"tranquillize": "tranquilize",
|
1605 |
+
"tranquillized": "tranquilized",
|
1606 |
+
"tranquillizer": "tranquilizer",
|
1607 |
+
"tranquillizers": "tranquilizers",
|
1608 |
+
"tranquillizes": "tranquilizes",
|
1609 |
+
"tranquillizing": "tranquilizing",
|
1610 |
+
"tranquilly": "tranquility",
|
1611 |
+
"transistorised": "transistorized",
|
1612 |
+
"traumatise": "traumatize",
|
1613 |
+
"traumatised": "traumatized",
|
1614 |
+
"traumatises": "traumatizes",
|
1615 |
+
"traumatising": "traumatizing",
|
1616 |
+
"travelled": "traveled",
|
1617 |
+
"traveller": "traveler",
|
1618 |
+
"travellers": "travelers",
|
1619 |
+
"travelling": "traveling",
|
1620 |
+
"travelog": "travelogue",
|
1621 |
+
"travelogs": "travelogues",
|
1622 |
+
"trialled": "trialed",
|
1623 |
+
"trialling": "trialing",
|
1624 |
+
"tricolour": "tricolor",
|
1625 |
+
"tricolours": "tricolors",
|
1626 |
+
"trivialise": "trivialize",
|
1627 |
+
"trivialised": "trivialized",
|
1628 |
+
"trivialises": "trivializes",
|
1629 |
+
"trivialising": "trivializing",
|
1630 |
+
"tumour": "tumor",
|
1631 |
+
"tumours": "tumors",
|
1632 |
+
"tunnelled": "tunneled",
|
1633 |
+
"tunnelling": "tunneling",
|
1634 |
+
"tyrannise": "tyrannize",
|
1635 |
+
"tyrannised": "tyrannized",
|
1636 |
+
"tyrannises": "tyrannizes",
|
1637 |
+
"tyrannising": "tyrannizing",
|
1638 |
+
"tyre": "tire",
|
1639 |
+
"tyres": "tires",
|
1640 |
+
"unauthorised": "unauthorized",
|
1641 |
+
"uncivilised": "uncivilized",
|
1642 |
+
"underutilised": "underutilized",
|
1643 |
+
"unequalled": "unequaled",
|
1644 |
+
"unfavourable": "unfavorable",
|
1645 |
+
"unfavourably": "unfavorably",
|
1646 |
+
"unionisation": "unionization",
|
1647 |
+
"unionise": "unionize",
|
1648 |
+
"unionised": "unionized",
|
1649 |
+
"unionises": "unionizes",
|
1650 |
+
"unionising": "unionizing",
|
1651 |
+
"unorganised": "unorganized",
|
1652 |
+
"unravelled": "unraveled",
|
1653 |
+
"unravelling": "unraveling",
|
1654 |
+
"unrecognisable": "unrecognizable",
|
1655 |
+
"unrecognised": "unrecognized",
|
1656 |
+
"unrivalled": "unrivaled",
|
1657 |
+
"unsavoury": "unsavory",
|
1658 |
+
"untrammelled": "untrammeled",
|
1659 |
+
"urbanisation": "urbanization",
|
1660 |
+
"urbanise": "urbanize",
|
1661 |
+
"urbanised": "urbanized",
|
1662 |
+
"urbanises": "urbanizes",
|
1663 |
+
"urbanising": "urbanizing",
|
1664 |
+
"utilisable": "utilizable",
|
1665 |
+
"utilisation": "utilization",
|
1666 |
+
"utilise": "utilize",
|
1667 |
+
"utilised": "utilized",
|
1668 |
+
"utilises": "utilizes",
|
1669 |
+
"utilising": "utilizing",
|
1670 |
+
"valour": "valor",
|
1671 |
+
"vandalise": "vandalize",
|
1672 |
+
"vandalised": "vandalized",
|
1673 |
+
"vandalises": "vandalizes",
|
1674 |
+
"vandalising": "vandalizing",
|
1675 |
+
"vaporisation": "vaporization",
|
1676 |
+
"vaporise": "vaporize",
|
1677 |
+
"vaporised": "vaporized",
|
1678 |
+
"vaporises": "vaporizes",
|
1679 |
+
"vaporising": "vaporizing",
|
1680 |
+
"vapour": "vapor",
|
1681 |
+
"vapours": "vapors",
|
1682 |
+
"verbalise": "verbalize",
|
1683 |
+
"verbalised": "verbalized",
|
1684 |
+
"verbalises": "verbalizes",
|
1685 |
+
"verbalising": "verbalizing",
|
1686 |
+
"victimisation": "victimization",
|
1687 |
+
"victimise": "victimize",
|
1688 |
+
"victimised": "victimized",
|
1689 |
+
"victimises": "victimizes",
|
1690 |
+
"victimising": "victimizing",
|
1691 |
+
"videodisc": "videodisk",
|
1692 |
+
"videodiscs": "videodisks",
|
1693 |
+
"vigour": "vigor",
|
1694 |
+
"visualisation": "visualization",
|
1695 |
+
"visualisations": "visualizations",
|
1696 |
+
"visualise": "visualize",
|
1697 |
+
"visualised": "visualized",
|
1698 |
+
"visualises": "visualizes",
|
1699 |
+
"visualising": "visualizing",
|
1700 |
+
"vocalisation": "vocalization",
|
1701 |
+
"vocalisations": "vocalizations",
|
1702 |
+
"vocalise": "vocalize",
|
1703 |
+
"vocalised": "vocalized",
|
1704 |
+
"vocalises": "vocalizes",
|
1705 |
+
"vocalising": "vocalizing",
|
1706 |
+
"vulcanised": "vulcanized",
|
1707 |
+
"vulgarisation": "vulgarization",
|
1708 |
+
"vulgarise": "vulgarize",
|
1709 |
+
"vulgarised": "vulgarized",
|
1710 |
+
"vulgarises": "vulgarizes",
|
1711 |
+
"vulgarising": "vulgarizing",
|
1712 |
+
"waggon": "wagon",
|
1713 |
+
"waggons": "wagons",
|
1714 |
+
"watercolour": "watercolor",
|
1715 |
+
"watercolours": "watercolors",
|
1716 |
+
"weaselled": "weaseled",
|
1717 |
+
"weaselling": "weaseling",
|
1718 |
+
"westernisation": "westernization",
|
1719 |
+
"westernise": "westernize",
|
1720 |
+
"westernised": "westernized",
|
1721 |
+
"westernises": "westernizes",
|
1722 |
+
"westernising": "westernizing",
|
1723 |
+
"womanise": "womanize",
|
1724 |
+
"womanised": "womanized",
|
1725 |
+
"womaniser": "womanizer",
|
1726 |
+
"womanisers": "womanizers",
|
1727 |
+
"womanises": "womanizes",
|
1728 |
+
"womanising": "womanizing",
|
1729 |
+
"woollen": "woolen",
|
1730 |
+
"woollens": "woolens",
|
1731 |
+
"woollies": "woolies",
|
1732 |
+
"woolly": "wooly",
|
1733 |
+
"worshipped": "worshiped",
|
1734 |
+
"worshipper": "worshiper",
|
1735 |
+
"worshipping": "worshiping",
|
1736 |
+
"yodelled": "yodeled",
|
1737 |
+
"yodelling": "yodeling",
|
1738 |
+
"yoghourt": "yogurt",
|
1739 |
+
"yoghourts": "yogurts",
|
1740 |
+
"yoghurt": "yogurt",
|
1741 |
+
"yoghurts": "yogurts"
|
1742 |
+
}
|
best_model/preprocessor_config.json
ADDED
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"chunk_length": 30,
|
3 |
+
"feature_extractor_type": "WhisperFeatureExtractor",
|
4 |
+
"feature_size": 80,
|
5 |
+
"hop_length": 160,
|
6 |
+
"n_fft": 400,
|
7 |
+
"n_samples": 480000,
|
8 |
+
"nb_max_frames": 3000,
|
9 |
+
"padding_side": "right",
|
10 |
+
"padding_value": 0.0,
|
11 |
+
"processor_class": "WhisperProcessor",
|
12 |
+
"return_attention_mask": false,
|
13 |
+
"sampling_rate": 16000
|
14 |
+
}
|
best_model/special_tokens_map.json
ADDED
@@ -0,0 +1,133 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
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|
|
|
|
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|
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|
|
|
|
|
|
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|
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|
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|
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|
|
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|
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|
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|
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|
|
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|
|
|
|
|
|
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|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"additional_special_tokens": [
|
3 |
+
"<|endoftext|>",
|
4 |
+
"<|startoftranscript|>",
|
5 |
+
"<|en|>",
|
6 |
+
"<|zh|>",
|
7 |
+
"<|de|>",
|
8 |
+
"<|es|>",
|
9 |
+
"<|ru|>",
|
10 |
+
"<|ko|>",
|
11 |
+
"<|fr|>",
|
12 |
+
"<|ja|>",
|
13 |
+
"<|pt|>",
|
14 |
+
"<|tr|>",
|
15 |
+
"<|pl|>",
|
16 |
+
"<|ca|>",
|
17 |
+
"<|nl|>",
|
18 |
+
"<|ar|>",
|
19 |
+
"<|sv|>",
|
20 |
+
"<|it|>",
|
21 |
+
"<|id|>",
|
22 |
+
"<|hi|>",
|
23 |
+
"<|fi|>",
|
24 |
+
"<|vi|>",
|
25 |
+
"<|he|>",
|
26 |
+
"<|uk|>",
|
27 |
+
"<|el|>",
|
28 |
+
"<|ms|>",
|
29 |
+
"<|cs|>",
|
30 |
+
"<|ro|>",
|
31 |
+
"<|da|>",
|
32 |
+
"<|hu|>",
|
33 |
+
"<|ta|>",
|
34 |
+
"<|no|>",
|
35 |
+
"<|th|>",
|
36 |
+
"<|ur|>",
|
37 |
+
"<|hr|>",
|
38 |
+
"<|bg|>",
|
39 |
+
"<|lt|>",
|
40 |
+
"<|la|>",
|
41 |
+
"<|mi|>",
|
42 |
+
"<|ml|>",
|
43 |
+
"<|cy|>",
|
44 |
+
"<|sk|>",
|
45 |
+
"<|te|>",
|
46 |
+
"<|fa|>",
|
47 |
+
"<|lv|>",
|
48 |
+
"<|bn|>",
|
49 |
+
"<|sr|>",
|
50 |
+
"<|az|>",
|
51 |
+
"<|sl|>",
|
52 |
+
"<|kn|>",
|
53 |
+
"<|et|>",
|
54 |
+
"<|mk|>",
|
55 |
+
"<|br|>",
|
56 |
+
"<|eu|>",
|
57 |
+
"<|is|>",
|
58 |
+
"<|hy|>",
|
59 |
+
"<|ne|>",
|
60 |
+
"<|mn|>",
|
61 |
+
"<|bs|>",
|
62 |
+
"<|kk|>",
|
63 |
+
"<|sq|>",
|
64 |
+
"<|sw|>",
|
65 |
+
"<|gl|>",
|
66 |
+
"<|mr|>",
|
67 |
+
"<|pa|>",
|
68 |
+
"<|si|>",
|
69 |
+
"<|km|>",
|
70 |
+
"<|sn|>",
|
71 |
+
"<|yo|>",
|
72 |
+
"<|so|>",
|
73 |
+
"<|af|>",
|
74 |
+
"<|oc|>",
|
75 |
+
"<|ka|>",
|
76 |
+
"<|be|>",
|
77 |
+
"<|tg|>",
|
78 |
+
"<|sd|>",
|
79 |
+
"<|gu|>",
|
80 |
+
"<|am|>",
|
81 |
+
"<|yi|>",
|
82 |
+
"<|lo|>",
|
83 |
+
"<|uz|>",
|
84 |
+
"<|fo|>",
|
85 |
+
"<|ht|>",
|
86 |
+
"<|ps|>",
|
87 |
+
"<|tk|>",
|
88 |
+
"<|nn|>",
|
89 |
+
"<|mt|>",
|
90 |
+
"<|sa|>",
|
91 |
+
"<|lb|>",
|
92 |
+
"<|my|>",
|
93 |
+
"<|bo|>",
|
94 |
+
"<|tl|>",
|
95 |
+
"<|mg|>",
|
96 |
+
"<|as|>",
|
97 |
+
"<|tt|>",
|
98 |
+
"<|haw|>",
|
99 |
+
"<|ln|>",
|
100 |
+
"<|ha|>",
|
101 |
+
"<|ba|>",
|
102 |
+
"<|jw|>",
|
103 |
+
"<|su|>",
|
104 |
+
"<|translate|>",
|
105 |
+
"<|transcribe|>",
|
106 |
+
"<|startoflm|>",
|
107 |
+
"<|startofprev|>",
|
108 |
+
"<|nocaptions|>",
|
109 |
+
"<|notimestamps|>"
|
110 |
+
],
|
111 |
+
"bos_token": {
|
112 |
+
"content": "<|endoftext|>",
|
113 |
+
"lstrip": false,
|
114 |
+
"normalized": true,
|
115 |
+
"rstrip": false,
|
116 |
+
"single_word": false
|
117 |
+
},
|
118 |
+
"eos_token": {
|
119 |
+
"content": "<|endoftext|>",
|
120 |
+
"lstrip": false,
|
121 |
+
"normalized": true,
|
122 |
+
"rstrip": false,
|
123 |
+
"single_word": false
|
124 |
+
},
|
125 |
+
"pad_token": "<|endoftext|>",
|
126 |
+
"unk_token": {
|
127 |
+
"content": "<|endoftext|>",
|
128 |
+
"lstrip": false,
|
129 |
+
"normalized": true,
|
130 |
+
"rstrip": false,
|
131 |
+
"single_word": false
|
132 |
+
}
|
133 |
+
}
|
best_model/tokenizer_config.json
ADDED
@@ -0,0 +1,35 @@
|
|
|
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|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"add_bos_token": false,
|
3 |
+
"add_prefix_space": false,
|
4 |
+
"bos_token": {
|
5 |
+
"__type": "AddedToken",
|
6 |
+
"content": "<|endoftext|>",
|
7 |
+
"lstrip": false,
|
8 |
+
"normalized": true,
|
9 |
+
"rstrip": false,
|
10 |
+
"single_word": false
|
11 |
+
},
|
12 |
+
"eos_token": {
|
13 |
+
"__type": "AddedToken",
|
14 |
+
"content": "<|endoftext|>",
|
15 |
+
"lstrip": false,
|
16 |
+
"normalized": true,
|
17 |
+
"rstrip": false,
|
18 |
+
"single_word": false
|
19 |
+
},
|
20 |
+
"errors": "replace",
|
21 |
+
"model_max_length": 1024,
|
22 |
+
"pad_token": null,
|
23 |
+
"processor_class": "WhisperProcessor",
|
24 |
+
"return_attention_mask": false,
|
25 |
+
"special_tokens_map_file": null,
|
26 |
+
"tokenizer_class": "WhisperTokenizer",
|
27 |
+
"unk_token": {
|
28 |
+
"__type": "AddedToken",
|
29 |
+
"content": "<|endoftext|>",
|
30 |
+
"lstrip": false,
|
31 |
+
"normalized": true,
|
32 |
+
"rstrip": false,
|
33 |
+
"single_word": false
|
34 |
+
}
|
35 |
+
}
|
best_model/vocab.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
config.json
ADDED
@@ -0,0 +1,51 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
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|
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|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "openai/whisper-small",
|
3 |
+
"activation_dropout": 0.0,
|
4 |
+
"activation_function": "gelu",
|
5 |
+
"apply_spec_augment": true,
|
6 |
+
"architectures": [
|
7 |
+
"WhisperForConditionalGeneration"
|
8 |
+
],
|
9 |
+
"attention_dropout": 0.0,
|
10 |
+
"begin_suppress_tokens": [
|
11 |
+
220,
|
12 |
+
50257
|
13 |
+
],
|
14 |
+
"bos_token_id": 50257,
|
15 |
+
"classifier_proj_size": 256,
|
16 |
+
"d_model": 768,
|
17 |
+
"decoder_attention_heads": 12,
|
18 |
+
"decoder_ffn_dim": 3072,
|
19 |
+
"decoder_layerdrop": 0.0,
|
20 |
+
"decoder_layers": 12,
|
21 |
+
"decoder_start_token_id": 50258,
|
22 |
+
"dropout": 0.1,
|
23 |
+
"encoder_attention_heads": 12,
|
24 |
+
"encoder_ffn_dim": 3072,
|
25 |
+
"encoder_layerdrop": 0.0,
|
26 |
+
"encoder_layers": 12,
|
27 |
+
"eos_token_id": 50257,
|
28 |
+
"forced_decoder_ids": null,
|
29 |
+
"init_std": 0.02,
|
30 |
+
"is_encoder_decoder": true,
|
31 |
+
"mask_feature_length": 10,
|
32 |
+
"mask_feature_min_masks": 0,
|
33 |
+
"mask_feature_prob": 0.0,
|
34 |
+
"mask_time_length": 10,
|
35 |
+
"mask_time_min_masks": 2,
|
36 |
+
"mask_time_prob": 0.05,
|
37 |
+
"max_length": 448,
|
38 |
+
"max_source_positions": 1500,
|
39 |
+
"max_target_positions": 448,
|
40 |
+
"model_type": "whisper",
|
41 |
+
"num_hidden_layers": 12,
|
42 |
+
"num_mel_bins": 80,
|
43 |
+
"pad_token_id": 50257,
|
44 |
+
"scale_embedding": false,
|
45 |
+
"suppress_tokens": [],
|
46 |
+
"torch_dtype": "float32",
|
47 |
+
"transformers_version": "4.28.0.dev0",
|
48 |
+
"use_cache": true,
|
49 |
+
"use_weighted_layer_sum": false,
|
50 |
+
"vocab_size": 51865
|
51 |
+
}
|
corrupt_files.txt
ADDED
@@ -0,0 +1,3718 @@
|
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1 |
+
# These files were identified has having issues due to failing text-audio alignment
|
2 |
+
# between reference transcript and audio.
|
3 |
+
|
4 |
+
common_voice_bn_30665285
|
5 |
+
common_voice_bn_30665286
|
6 |
+
common_voice_bn_30665287
|
7 |
+
common_voice_bn_30665288
|
8 |
+
common_voice_bn_30665290
|
9 |
+
common_voice_bn_30665291
|
10 |
+
common_voice_bn_30665294
|
11 |
+
common_voice_bn_30665295
|
12 |
+
common_voice_bn_30665296
|
13 |
+
common_voice_bn_30665297
|
14 |
+
common_voice_bn_30665298
|
15 |
+
common_voice_bn_30677291
|
16 |
+
common_voice_bn_30677292
|
17 |
+
common_voice_bn_30677293
|
18 |
+
common_voice_bn_30677294
|
19 |
+
common_voice_bn_30677295
|
20 |
+
common_voice_bn_30995469
|
21 |
+
common_voice_bn_30995470
|
22 |
+
common_voice_bn_30998934
|
23 |
+
common_voice_bn_31000747
|
24 |
+
common_voice_bn_31000750
|
25 |
+
common_voice_bn_31000753
|
26 |
+
common_voice_bn_31005676
|
27 |
+
common_voice_bn_31005686
|
28 |
+
common_voice_bn_31009001
|
29 |
+
common_voice_bn_31011206
|
30 |
+
common_voice_bn_31013329
|
31 |
+
common_voice_bn_31013418
|
32 |
+
common_voice_bn_31016821
|
33 |
+
common_voice_bn_31016823
|
34 |
+
common_voice_bn_31016825
|
35 |
+
common_voice_bn_31016831
|
36 |
+
common_voice_bn_31019660
|
37 |
+
common_voice_bn_31019914
|
38 |
+
common_voice_bn_31021589
|
39 |
+
common_voice_bn_31021790
|
40 |
+
common_voice_bn_31021831
|
41 |
+
common_voice_bn_31021833
|
42 |
+
common_voice_bn_31021834
|
43 |
+
common_voice_bn_31021835
|
44 |
+
common_voice_bn_31021847
|
45 |
+
common_voice_bn_31021861
|
46 |
+
common_voice_bn_31025585
|
47 |
+
common_voice_bn_31026100
|
48 |
+
common_voice_bn_31037299
|
49 |
+
common_voice_bn_31043545
|
50 |
+
common_voice_bn_31052304
|
51 |
+
common_voice_bn_31174226
|
52 |
+
common_voice_bn_31174227
|
53 |
+
common_voice_bn_31217111
|
54 |
+
common_voice_bn_31277603
|
55 |
+
common_voice_bn_31362334
|
56 |
+
common_voice_bn_31445621
|
57 |
+
common_voice_bn_31497795
|
58 |
+
common_voice_bn_31498452
|
59 |
+
common_voice_bn_31498453
|
60 |
+
common_voice_bn_31498455
|
61 |
+
common_voice_bn_31498456
|
62 |
+
common_voice_bn_31498467
|
63 |
+
common_voice_bn_31498469
|
64 |
+
common_voice_bn_31498470
|
65 |
+
common_voice_bn_31498471
|
66 |
+
common_voice_bn_31500246
|
67 |
+
common_voice_bn_31500248
|
68 |
+
common_voice_bn_31500250
|
69 |
+
common_voice_bn_31500370
|
70 |
+
common_voice_bn_31500372
|
71 |
+
common_voice_bn_31500374
|
72 |
+
common_voice_bn_31500444
|
73 |
+
common_voice_bn_31500446
|
74 |
+
common_voice_bn_31500447
|
75 |
+
common_voice_bn_31500509
|
76 |
+
common_voice_bn_31500511
|
77 |
+
common_voice_bn_31500805
|
78 |
+
common_voice_bn_31508353
|
79 |
+
common_voice_bn_31508469
|
80 |
+
common_voice_bn_31508593
|
81 |
+
common_voice_bn_31508596
|
82 |
+
common_voice_bn_31508652
|
83 |
+
common_voice_bn_31508719
|
84 |
+
common_voice_bn_31508987
|
85 |
+
common_voice_bn_31508990
|
86 |
+
common_voice_bn_31509003
|
87 |
+
common_voice_bn_31509014
|
88 |
+
common_voice_bn_31509079
|
89 |
+
common_voice_bn_31509152
|
90 |
+
common_voice_bn_31509201
|
91 |
+
common_voice_bn_31509256
|
92 |
+
common_voice_bn_31509356
|
93 |
+
common_voice_bn_31509610
|
94 |
+
common_voice_bn_31509722
|
95 |
+
common_voice_bn_31509753
|
96 |
+
common_voice_bn_31509771
|
97 |
+
common_voice_bn_31509803
|
98 |
+
common_voice_bn_31509808
|
99 |
+
common_voice_bn_31509879
|
100 |
+
common_voice_bn_31509983
|
101 |
+
common_voice_bn_31510143
|
102 |
+
common_voice_bn_31510163
|
103 |
+
common_voice_bn_31510205
|
104 |
+
common_voice_bn_31510212
|
105 |
+
common_voice_bn_31510219
|
106 |
+
common_voice_bn_31510223
|
107 |
+
common_voice_bn_31510388
|
108 |
+
common_voice_bn_31510468
|
109 |
+
common_voice_bn_31510520
|
110 |
+
common_voice_bn_31510909
|
111 |
+
common_voice_bn_31511001
|
112 |
+
common_voice_bn_31511003
|
113 |
+
common_voice_bn_31511028
|
114 |
+
common_voice_bn_31511211
|
115 |
+
common_voice_bn_31511213
|
116 |
+
common_voice_bn_31511298
|
117 |
+
common_voice_bn_31511365
|
118 |
+
common_voice_bn_31511378
|
119 |
+
common_voice_bn_31511414
|
120 |
+
common_voice_bn_31511666
|
121 |
+
common_voice_bn_31511748
|
122 |
+
common_voice_bn_31511759
|
123 |
+
common_voice_bn_31511859
|
124 |
+
common_voice_bn_31512000
|
125 |
+
common_voice_bn_31512004
|
126 |
+
common_voice_bn_31512204
|
127 |
+
common_voice_bn_31512403
|
128 |
+
common_voice_bn_31512543
|
129 |
+
common_voice_bn_31512550
|
130 |
+
common_voice_bn_31512816
|
131 |
+
common_voice_bn_31512818
|
132 |
+
common_voice_bn_31512832
|
133 |
+
common_voice_bn_31513134
|
134 |
+
common_voice_bn_31513221
|
135 |
+
common_voice_bn_31513229
|
136 |
+
common_voice_bn_31513256
|
137 |
+
common_voice_bn_31513270
|
138 |
+
common_voice_bn_31513308
|
139 |
+
common_voice_bn_31513356
|
140 |
+
common_voice_bn_31513517
|
141 |
+
common_voice_bn_31513590
|
142 |
+
common_voice_bn_31513841
|
143 |
+
common_voice_bn_31513896
|
144 |
+
common_voice_bn_31513922
|
145 |
+
common_voice_bn_31513951
|
146 |
+
common_voice_bn_31513994
|
147 |
+
common_voice_bn_31514003
|
148 |
+
common_voice_bn_31514010
|
149 |
+
common_voice_bn_31514021
|
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3487 |
+
common_voice_bn_31772222
|
3488 |
+
common_voice_bn_31772223
|
3489 |
+
common_voice_bn_31772265
|
3490 |
+
common_voice_bn_31772266
|
3491 |
+
common_voice_bn_31772346
|
3492 |
+
common_voice_bn_31772398
|
3493 |
+
common_voice_bn_31772399
|
3494 |
+
common_voice_bn_31772400
|
3495 |
+
common_voice_bn_31772404
|
3496 |
+
common_voice_bn_31772652
|
3497 |
+
common_voice_bn_31772653
|
3498 |
+
common_voice_bn_31772654
|
3499 |
+
common_voice_bn_31772655
|
3500 |
+
common_voice_bn_31772656
|
3501 |
+
common_voice_bn_31772672
|
3502 |
+
common_voice_bn_31772892
|
3503 |
+
common_voice_bn_31772972
|
3504 |
+
common_voice_bn_31773505
|
3505 |
+
common_voice_bn_31773535
|
3506 |
+
common_voice_bn_31773539
|
3507 |
+
common_voice_bn_31773651
|
3508 |
+
common_voice_bn_31773653
|
3509 |
+
common_voice_bn_31773655
|
3510 |
+
common_voice_bn_31773657
|
3511 |
+
common_voice_bn_31773659
|
3512 |
+
common_voice_bn_31773758
|
3513 |
+
common_voice_bn_31773760
|
3514 |
+
common_voice_bn_31773761
|
3515 |
+
common_voice_bn_31773812
|
3516 |
+
common_voice_bn_31773855
|
3517 |
+
common_voice_bn_31773913
|
3518 |
+
common_voice_bn_31773946
|
3519 |
+
common_voice_bn_31774320
|
3520 |
+
common_voice_bn_31774502
|
3521 |
+
common_voice_bn_31774544
|
3522 |
+
common_voice_bn_31774547
|
3523 |
+
common_voice_bn_31775860
|
3524 |
+
common_voice_bn_31775861
|
3525 |
+
common_voice_bn_31775862
|
3526 |
+
common_voice_bn_31775864
|
3527 |
+
common_voice_bn_31775886
|
3528 |
+
common_voice_bn_31775888
|
3529 |
+
common_voice_bn_31775889
|
3530 |
+
common_voice_bn_31775891
|
3531 |
+
common_voice_bn_31775893
|
3532 |
+
common_voice_bn_31775960
|
3533 |
+
common_voice_bn_31776246
|
3534 |
+
common_voice_bn_31776372
|
3535 |
+
common_voice_bn_31776435
|
3536 |
+
common_voice_bn_31776457
|
3537 |
+
common_voice_bn_31776459
|
3538 |
+
common_voice_bn_31776460
|
3539 |
+
common_voice_bn_31776461
|
3540 |
+
common_voice_bn_31776568
|
3541 |
+
common_voice_bn_31776700
|
3542 |
+
common_voice_bn_31777342
|
3543 |
+
common_voice_bn_31777802
|
3544 |
+
common_voice_bn_31777848
|
3545 |
+
common_voice_bn_31777864
|
3546 |
+
common_voice_bn_31777865
|
3547 |
+
common_voice_bn_31777868
|
3548 |
+
common_voice_bn_31777920
|
3549 |
+
common_voice_bn_31778016
|
3550 |
+
common_voice_bn_31778368
|
3551 |
+
common_voice_bn_31778691
|
3552 |
+
common_voice_bn_31778693
|
3553 |
+
common_voice_bn_31778886
|
3554 |
+
common_voice_bn_31779197
|
3555 |
+
common_voice_bn_31779659
|
3556 |
+
common_voice_bn_31779765
|
3557 |
+
common_voice_bn_31779767
|
3558 |
+
common_voice_bn_31780047
|
3559 |
+
common_voice_bn_31780049
|
3560 |
+
common_voice_bn_31780501
|
3561 |
+
common_voice_bn_31780589
|
3562 |
+
common_voice_bn_31780792
|
3563 |
+
common_voice_bn_31780840
|
3564 |
+
common_voice_bn_31780976
|
3565 |
+
common_voice_bn_31781084
|
3566 |
+
common_voice_bn_31781605
|
3567 |
+
common_voice_bn_31782044
|
3568 |
+
common_voice_bn_31782079
|
3569 |
+
common_voice_bn_31783553
|
3570 |
+
common_voice_bn_31784057
|
3571 |
+
common_voice_bn_31784318
|
3572 |
+
common_voice_bn_31784333
|
3573 |
+
common_voice_bn_31784384
|
3574 |
+
common_voice_bn_31784538
|
3575 |
+
common_voice_bn_31784564
|
3576 |
+
common_voice_bn_31784566
|
3577 |
+
common_voice_bn_31785133
|
3578 |
+
common_voice_bn_31785212
|
3579 |
+
common_voice_bn_31785249
|
3580 |
+
common_voice_bn_31785528
|
3581 |
+
common_voice_bn_31785667
|
3582 |
+
common_voice_bn_31785668
|
3583 |
+
common_voice_bn_31785944
|
3584 |
+
common_voice_bn_31785979
|
3585 |
+
common_voice_bn_31785980
|
3586 |
+
common_voice_bn_31785981
|
3587 |
+
common_voice_bn_31786203
|
3588 |
+
common_voice_bn_31786217
|
3589 |
+
common_voice_bn_31786281
|
3590 |
+
common_voice_bn_31786282
|
3591 |
+
common_voice_bn_31786283
|
3592 |
+
common_voice_bn_31786285
|
3593 |
+
common_voice_bn_31786367
|
3594 |
+
common_voice_bn_31786516
|
3595 |
+
common_voice_bn_31786519
|
3596 |
+
common_voice_bn_31786520
|
3597 |
+
common_voice_bn_31786521
|
3598 |
+
common_voice_bn_31786522
|
3599 |
+
common_voice_bn_31786845
|
3600 |
+
common_voice_bn_31787124
|
3601 |
+
common_voice_bn_31787691
|
3602 |
+
common_voice_bn_31788045
|
3603 |
+
common_voice_bn_31788130
|
3604 |
+
common_voice_bn_31788418
|
3605 |
+
common_voice_bn_31788513
|
3606 |
+
common_voice_bn_31788515
|
3607 |
+
common_voice_bn_31788516
|
3608 |
+
common_voice_bn_31788673
|
3609 |
+
common_voice_bn_31789054
|
3610 |
+
common_voice_bn_31789055
|
3611 |
+
common_voice_bn_31789056
|
3612 |
+
common_voice_bn_31789392
|
3613 |
+
common_voice_bn_31789393
|
3614 |
+
common_voice_bn_31789394
|
3615 |
+
common_voice_bn_31789395
|
3616 |
+
common_voice_bn_31789397
|
3617 |
+
common_voice_bn_31789475
|
3618 |
+
common_voice_bn_31789476
|
3619 |
+
common_voice_bn_31789477
|
3620 |
+
common_voice_bn_31789478
|
3621 |
+
common_voice_bn_31789479
|
3622 |
+
common_voice_bn_31789669
|
3623 |
+
common_voice_bn_31789694
|
3624 |
+
common_voice_bn_31790059
|
3625 |
+
common_voice_bn_31791040
|
3626 |
+
common_voice_bn_31791041
|
3627 |
+
common_voice_bn_31791043
|
3628 |
+
common_voice_bn_31791044
|
3629 |
+
common_voice_bn_31791090
|
3630 |
+
common_voice_bn_31791092
|
3631 |
+
common_voice_bn_31791138
|
3632 |
+
common_voice_bn_31791139
|
3633 |
+
common_voice_bn_31791140
|
3634 |
+
common_voice_bn_31791141
|
3635 |
+
common_voice_bn_31791142
|
3636 |
+
common_voice_bn_31791910
|
3637 |
+
common_voice_bn_31791987
|
3638 |
+
common_voice_bn_31792072
|
3639 |
+
common_voice_bn_31793357
|
3640 |
+
common_voice_bn_31793766
|
3641 |
+
common_voice_bn_31794478
|
3642 |
+
common_voice_bn_31794575
|
3643 |
+
common_voice_bn_31796218
|
3644 |
+
common_voice_bn_31796716
|
3645 |
+
common_voice_bn_31797835
|
3646 |
+
common_voice_bn_31797836
|
3647 |
+
common_voice_bn_31798447
|
3648 |
+
common_voice_bn_31798570
|
3649 |
+
common_voice_bn_31799923
|
3650 |
+
common_voice_bn_31800225
|
3651 |
+
common_voice_bn_31802483
|
3652 |
+
common_voice_bn_31803201
|
3653 |
+
common_voice_bn_31803980
|
3654 |
+
common_voice_bn_31804361
|
3655 |
+
common_voice_bn_31805137
|
3656 |
+
common_voice_bn_31805387
|
3657 |
+
common_voice_bn_31805441
|
3658 |
+
common_voice_bn_31805468
|
3659 |
+
common_voice_bn_31806488
|
3660 |
+
common_voice_bn_31806490
|
3661 |
+
common_voice_bn_31807719
|
3662 |
+
common_voice_bn_31808188
|
3663 |
+
common_voice_bn_31809237
|
3664 |
+
common_voice_bn_31810075
|
3665 |
+
common_voice_bn_31810245
|
3666 |
+
common_voice_bn_31810246
|
3667 |
+
common_voice_bn_31810247
|
3668 |
+
common_voice_bn_31810248
|
3669 |
+
common_voice_bn_31810249
|
3670 |
+
common_voice_bn_31810418
|
3671 |
+
common_voice_bn_31810435
|
3672 |
+
common_voice_bn_31810437
|
3673 |
+
common_voice_bn_31810438
|
3674 |
+
common_voice_bn_31810693
|
3675 |
+
common_voice_bn_31810714
|
3676 |
+
common_voice_bn_31811341
|
3677 |
+
common_voice_bn_31811425
|
3678 |
+
common_voice_bn_31811494
|
3679 |
+
common_voice_bn_31811511
|
3680 |
+
common_voice_bn_31811533
|
3681 |
+
common_voice_bn_31811914
|
3682 |
+
common_voice_bn_31815179
|
3683 |
+
common_voice_bn_31815991
|
3684 |
+
common_voice_bn_31816315
|
3685 |
+
common_voice_bn_31816316
|
3686 |
+
common_voice_bn_31816710
|
3687 |
+
common_voice_bn_31817036
|
3688 |
+
common_voice_bn_31817037
|
3689 |
+
common_voice_bn_31817038
|
3690 |
+
common_voice_bn_31817090
|
3691 |
+
common_voice_bn_31817127
|
3692 |
+
common_voice_bn_31817130
|
3693 |
+
common_voice_bn_31817132
|
3694 |
+
common_voice_bn_31817134
|
3695 |
+
common_voice_bn_31817159
|
3696 |
+
common_voice_bn_31818272
|
3697 |
+
common_voice_bn_31818995
|
3698 |
+
common_voice_bn_31818996
|
3699 |
+
common_voice_bn_31818997
|
3700 |
+
common_voice_bn_31818998
|
3701 |
+
common_voice_bn_31818999
|
3702 |
+
common_voice_bn_31819000
|
3703 |
+
common_voice_bn_31819001
|
3704 |
+
common_voice_bn_31819002
|
3705 |
+
common_voice_bn_31819004
|
3706 |
+
common_voice_bn_31819251
|
3707 |
+
common_voice_bn_31819471
|
3708 |
+
common_voice_bn_31819565
|
3709 |
+
common_voice_bn_31820299
|
3710 |
+
common_voice_bn_31828135
|
3711 |
+
common_voice_bn_31828948
|
3712 |
+
common_voice_bn_31828950
|
3713 |
+
common_voice_bn_31828952
|
3714 |
+
common_voice_bn_31828954
|
3715 |
+
common_voice_bn_31828955
|
3716 |
+
common_voice_bn_31831117
|
3717 |
+
common_voice_bn_31831119
|
3718 |
+
common_voice_bn_31832651
|
eval-args.txt
ADDED
@@ -0,0 +1,63 @@
|
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|
|
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|
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|
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|
|
|
|
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|
|
|
|
|
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|
|
|
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|
|
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|
|
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|
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|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
|
2 |
+
## Generates eval.sh for testing if script works
|
3 |
+
echo 'python my-evaluation.py \
|
4 |
+
--model_id="openai/whisper-tiny" \
|
5 |
+
--dataset="google/fleurs" \
|
6 |
+
--config="bn_in" \
|
7 |
+
--language="bn" \
|
8 |
+
--split="test" \
|
9 |
+
--max_eval_samples="50" \
|
10 |
+
--batch_size="16" \
|
11 |
+
--do_bangla_unicode_normalize="True" \
|
12 |
+
--device="0" \
|
13 |
+
--streaming="False"' >> eval.sh
|
14 |
+
|
15 |
+
## Evaluates on google/fleurs test set
|
16 |
+
echo 'python my-evaluation.py \
|
17 |
+
--model_id="openai/whisper-small-bn-all-400" \
|
18 |
+
--dataset="google/fleurs" \
|
19 |
+
--config="bn_in" \
|
20 |
+
--language="bn" \
|
21 |
+
--split="test" \
|
22 |
+
--batch_size="16" \
|
23 |
+
--do_bangla_unicode_normalize="True" \
|
24 |
+
--device="0" \
|
25 |
+
--streaming="False"' >> eval.sh
|
26 |
+
|
27 |
+
## Evaluates on common voice 11.0
|
28 |
+
echo 'python my-evaluation.py \
|
29 |
+
--model_id="openai/whisper-small-bn-all-400" \
|
30 |
+
--dataset="mozilla-foundation/common_voice_11_0" \
|
31 |
+
--config="bn" \
|
32 |
+
--language="bn" \
|
33 |
+
--split="test" \
|
34 |
+
--batch_size="16" \
|
35 |
+
--do_bangla_unicode_normalize="True" \
|
36 |
+
--device="0" \
|
37 |
+
--streaming="False"' >> eval.sh
|
38 |
+
|
39 |
+
## Evaluates on openslr 53
|
40 |
+
echo 'python my-evaluation.py \
|
41 |
+
--model_id="openai/whisper-small-bn-all-400" \
|
42 |
+
--dataset="openslr" \
|
43 |
+
--config="SLR53" \
|
44 |
+
--language="bn" \
|
45 |
+
--split="test" \
|
46 |
+
--batch_size="16" \
|
47 |
+
--do_bangla_unicode_normalize="True" \
|
48 |
+
--device="0" \
|
49 |
+
--streaming="False"' >> eval.sh
|
50 |
+
|
51 |
+
|
52 |
+
|
53 |
+
|
54 |
+
#max_eval_samples MAX_EVAL_SAMPLES. Number of samples to be evaluated. Put a lower number e.g. 64 for testing this script.
|
55 |
+
#(default: None)
|
56 |
+
|
57 |
+
--max_eval_samples="50"
|
58 |
+
|
59 |
+
|
60 |
+
|
61 |
+
|
62 |
+
|
63 |
+
|
eval.sh
ADDED
@@ -0,0 +1,11 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
python my-evaluation.py \
|
2 |
+
--model_id="openai/whisper-tiny" \
|
3 |
+
--dataset="google/fleurs" \
|
4 |
+
--config="bn_in" \
|
5 |
+
--language="bn" \
|
6 |
+
--split="test" \
|
7 |
+
--max_eval_samples="50" \
|
8 |
+
--batch_size="16" \
|
9 |
+
--do_bangla_unicode_normalize="True" \
|
10 |
+
--device="0" \
|
11 |
+
--streaming="False"
|
eval_results.json
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"epoch": 1.31,
|
3 |
+
"eval_cer": 304.78184991274,
|
4 |
+
"eval_loss": 1.9569354057312012,
|
5 |
+
"eval_runtime": 28.0459,
|
6 |
+
"eval_samples_per_second": 1.783,
|
7 |
+
"eval_steps_per_second": 0.071,
|
8 |
+
"eval_wer": 369.68
|
9 |
+
}
|
generation_config.json
ADDED
@@ -0,0 +1,222 @@
|
|
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|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"begin_suppress_tokens": [
|
3 |
+
220,
|
4 |
+
50257
|
5 |
+
],
|
6 |
+
"bos_token_id": 50257,
|
7 |
+
"decoder_start_token_id": 50258,
|
8 |
+
"eos_token_id": 50257,
|
9 |
+
"forced_decoder_ids": [
|
10 |
+
[
|
11 |
+
1,
|
12 |
+
null
|
13 |
+
],
|
14 |
+
[
|
15 |
+
2,
|
16 |
+
50359
|
17 |
+
]
|
18 |
+
],
|
19 |
+
"is_multilingual": true,
|
20 |
+
"lang_to_id": {
|
21 |
+
"<|af|>": 50327,
|
22 |
+
"<|am|>": 50334,
|
23 |
+
"<|ar|>": 50272,
|
24 |
+
"<|as|>": 50350,
|
25 |
+
"<|az|>": 50304,
|
26 |
+
"<|ba|>": 50355,
|
27 |
+
"<|be|>": 50330,
|
28 |
+
"<|bg|>": 50292,
|
29 |
+
"<|bn|>": 50302,
|
30 |
+
"<|bo|>": 50347,
|
31 |
+
"<|br|>": 50309,
|
32 |
+
"<|bs|>": 50315,
|
33 |
+
"<|ca|>": 50270,
|
34 |
+
"<|cs|>": 50283,
|
35 |
+
"<|cy|>": 50297,
|
36 |
+
"<|da|>": 50285,
|
37 |
+
"<|de|>": 50261,
|
38 |
+
"<|el|>": 50281,
|
39 |
+
"<|en|>": 50259,
|
40 |
+
"<|es|>": 50262,
|
41 |
+
"<|et|>": 50307,
|
42 |
+
"<|eu|>": 50310,
|
43 |
+
"<|fa|>": 50300,
|
44 |
+
"<|fi|>": 50277,
|
45 |
+
"<|fo|>": 50338,
|
46 |
+
"<|fr|>": 50265,
|
47 |
+
"<|gl|>": 50319,
|
48 |
+
"<|gu|>": 50333,
|
49 |
+
"<|haw|>": 50352,
|
50 |
+
"<|ha|>": 50354,
|
51 |
+
"<|he|>": 50279,
|
52 |
+
"<|hi|>": 50276,
|
53 |
+
"<|hr|>": 50291,
|
54 |
+
"<|ht|>": 50339,
|
55 |
+
"<|hu|>": 50286,
|
56 |
+
"<|hy|>": 50312,
|
57 |
+
"<|id|>": 50275,
|
58 |
+
"<|is|>": 50311,
|
59 |
+
"<|it|>": 50274,
|
60 |
+
"<|ja|>": 50266,
|
61 |
+
"<|jw|>": 50356,
|
62 |
+
"<|ka|>": 50329,
|
63 |
+
"<|kk|>": 50316,
|
64 |
+
"<|km|>": 50323,
|
65 |
+
"<|kn|>": 50306,
|
66 |
+
"<|ko|>": 50264,
|
67 |
+
"<|la|>": 50294,
|
68 |
+
"<|lb|>": 50345,
|
69 |
+
"<|ln|>": 50353,
|
70 |
+
"<|lo|>": 50336,
|
71 |
+
"<|lt|>": 50293,
|
72 |
+
"<|lv|>": 50301,
|
73 |
+
"<|mg|>": 50349,
|
74 |
+
"<|mi|>": 50295,
|
75 |
+
"<|mk|>": 50308,
|
76 |
+
"<|ml|>": 50296,
|
77 |
+
"<|mn|>": 50314,
|
78 |
+
"<|mr|>": 50320,
|
79 |
+
"<|ms|>": 50282,
|
80 |
+
"<|mt|>": 50343,
|
81 |
+
"<|my|>": 50346,
|
82 |
+
"<|ne|>": 50313,
|
83 |
+
"<|nl|>": 50271,
|
84 |
+
"<|nn|>": 50342,
|
85 |
+
"<|no|>": 50288,
|
86 |
+
"<|oc|>": 50328,
|
87 |
+
"<|pa|>": 50321,
|
88 |
+
"<|pl|>": 50269,
|
89 |
+
"<|ps|>": 50340,
|
90 |
+
"<|pt|>": 50267,
|
91 |
+
"<|ro|>": 50284,
|
92 |
+
"<|ru|>": 50263,
|
93 |
+
"<|sa|>": 50344,
|
94 |
+
"<|sd|>": 50332,
|
95 |
+
"<|si|>": 50322,
|
96 |
+
"<|sk|>": 50298,
|
97 |
+
"<|sl|>": 50305,
|
98 |
+
"<|sn|>": 50324,
|
99 |
+
"<|so|>": 50326,
|
100 |
+
"<|sq|>": 50317,
|
101 |
+
"<|sr|>": 50303,
|
102 |
+
"<|su|>": 50357,
|
103 |
+
"<|sv|>": 50273,
|
104 |
+
"<|sw|>": 50318,
|
105 |
+
"<|ta|>": 50287,
|
106 |
+
"<|te|>": 50299,
|
107 |
+
"<|tg|>": 50331,
|
108 |
+
"<|th|>": 50289,
|
109 |
+
"<|tk|>": 50341,
|
110 |
+
"<|tl|>": 50348,
|
111 |
+
"<|tr|>": 50268,
|
112 |
+
"<|tt|>": 50351,
|
113 |
+
"<|uk|>": 50280,
|
114 |
+
"<|ur|>": 50290,
|
115 |
+
"<|uz|>": 50337,
|
116 |
+
"<|vi|>": 50278,
|
117 |
+
"<|yi|>": 50335,
|
118 |
+
"<|yo|>": 50325,
|
119 |
+
"<|zh|>": 50260
|
120 |
+
},
|
121 |
+
"max_initial_timestamp_index": 1,
|
122 |
+
"max_length": 448,
|
123 |
+
"max_new_tokens": 448,
|
124 |
+
"no_timestamps_token_id": 50363,
|
125 |
+
"pad_token_id": 50257,
|
126 |
+
"return_timestamps": false,
|
127 |
+
"suppress_tokens": [
|
128 |
+
1,
|
129 |
+
2,
|
130 |
+
7,
|
131 |
+
8,
|
132 |
+
9,
|
133 |
+
10,
|
134 |
+
14,
|
135 |
+
25,
|
136 |
+
26,
|
137 |
+
27,
|
138 |
+
28,
|
139 |
+
29,
|
140 |
+
31,
|
141 |
+
58,
|
142 |
+
59,
|
143 |
+
60,
|
144 |
+
61,
|
145 |
+
62,
|
146 |
+
63,
|
147 |
+
90,
|
148 |
+
91,
|
149 |
+
92,
|
150 |
+
93,
|
151 |
+
359,
|
152 |
+
503,
|
153 |
+
522,
|
154 |
+
542,
|
155 |
+
873,
|
156 |
+
893,
|
157 |
+
902,
|
158 |
+
918,
|
159 |
+
922,
|
160 |
+
931,
|
161 |
+
1350,
|
162 |
+
1853,
|
163 |
+
1982,
|
164 |
+
2460,
|
165 |
+
2627,
|
166 |
+
3246,
|
167 |
+
3253,
|
168 |
+
3268,
|
169 |
+
3536,
|
170 |
+
3846,
|
171 |
+
3961,
|
172 |
+
4183,
|
173 |
+
4667,
|
174 |
+
6585,
|
175 |
+
6647,
|
176 |
+
7273,
|
177 |
+
9061,
|
178 |
+
9383,
|
179 |
+
10428,
|
180 |
+
10929,
|
181 |
+
11938,
|
182 |
+
12033,
|
183 |
+
12331,
|
184 |
+
12562,
|
185 |
+
13793,
|
186 |
+
14157,
|
187 |
+
14635,
|
188 |
+
15265,
|
189 |
+
15618,
|
190 |
+
16553,
|
191 |
+
16604,
|
192 |
+
18362,
|
193 |
+
18956,
|
194 |
+
20075,
|
195 |
+
21675,
|
196 |
+
22520,
|
197 |
+
26130,
|
198 |
+
26161,
|
199 |
+
26435,
|
200 |
+
28279,
|
201 |
+
29464,
|
202 |
+
31650,
|
203 |
+
32302,
|
204 |
+
32470,
|
205 |
+
36865,
|
206 |
+
42863,
|
207 |
+
47425,
|
208 |
+
49870,
|
209 |
+
50254,
|
210 |
+
50258,
|
211 |
+
50358,
|
212 |
+
50359,
|
213 |
+
50360,
|
214 |
+
50361,
|
215 |
+
50362
|
216 |
+
],
|
217 |
+
"task_to_id": {
|
218 |
+
"transcribe": 50359,
|
219 |
+
"translate": 50358
|
220 |
+
},
|
221 |
+
"transformers_version": "4.28.0.dev0"
|
222 |
+
}
|
merges.txt
ADDED
The diff for this file is too large to render.
See raw diff
|
|
my-evaluation.py
ADDED
@@ -0,0 +1,237 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import argparse
|
2 |
+
import os
|
3 |
+
from regex import R
|
4 |
+
|
5 |
+
abs_path = os.path.abspath('.')
|
6 |
+
# base_dir = os.path.dirname(os.path.dirname(abs_path))
|
7 |
+
base_dir = os.path.dirname(abs_path)
|
8 |
+
|
9 |
+
|
10 |
+
os.environ['TRANSFORMERS_CACHE'] = os.path.join(base_dir, 'models_cache')
|
11 |
+
os.environ['TRANSFORMERS_OFFLINE'] = '0'
|
12 |
+
os.environ['HF_DATASETS_CACHE'] = os.path.join(base_dir, 'datasets_cache')
|
13 |
+
os.environ['HF_DATASETS_OFFLINE'] = '0'
|
14 |
+
|
15 |
+
from transformers import pipeline
|
16 |
+
from transformers.models.whisper.english_normalizer import BasicTextNormalizer
|
17 |
+
from datasets import load_dataset, Audio
|
18 |
+
from bnunicodenormalizer import Normalizer
|
19 |
+
import evaluate
|
20 |
+
import unicodedata
|
21 |
+
|
22 |
+
wer_metric = evaluate.load("wer", cache_dir=os.path.join(base_dir, "metrics_cache"))
|
23 |
+
cer_metric = evaluate.load("cer", cache_dir=os.path.join(base_dir, "metrics_cache"))
|
24 |
+
|
25 |
+
|
26 |
+
def is_target_text_in_range(ref):
|
27 |
+
if ref.strip() == "ignore time segment in scoring":
|
28 |
+
return False
|
29 |
+
else:
|
30 |
+
return ref.strip() != ""
|
31 |
+
|
32 |
+
|
33 |
+
def get_text(sample):
|
34 |
+
if "text" in sample:
|
35 |
+
return sample["text"]
|
36 |
+
elif "sentence" in sample:
|
37 |
+
return sample["sentence"]
|
38 |
+
elif "normalized_text" in sample:
|
39 |
+
return sample["normalized_text"]
|
40 |
+
elif "transcript" in sample:
|
41 |
+
return sample["transcript"]
|
42 |
+
elif "transcription" in sample:
|
43 |
+
return sample["transcription"]
|
44 |
+
else:
|
45 |
+
raise ValueError(
|
46 |
+
"Expected transcript column of either 'text', 'sentence', 'normalized_text' or 'transcript'. Got sample of "
|
47 |
+
".join{sample.keys()}. Ensure a text column name is present in the dataset."
|
48 |
+
)
|
49 |
+
|
50 |
+
|
51 |
+
whisper_norm = BasicTextNormalizer()
|
52 |
+
bangla_normalizer = Normalizer(allow_english=True)
|
53 |
+
|
54 |
+
|
55 |
+
def normalise(batch):
|
56 |
+
batch["norm_text"] = whisper_norm(get_text(batch))
|
57 |
+
return batch
|
58 |
+
|
59 |
+
def removeOptionalZW(text):
|
60 |
+
"""
|
61 |
+
Removes all optional occurrences of ZWNJ or ZWJ from Bangla text.
|
62 |
+
"""
|
63 |
+
# Regex for matching zero witdh joiner variations.
|
64 |
+
STANDARDIZE_ZW = re.compile(r'(?<=\u09b0)[\u200c\u200d]+(?=\u09cd\u09af)')
|
65 |
+
|
66 |
+
# Regex for removing standardized zero width joiner, except in edge cases.
|
67 |
+
DELETE_ZW = re.compile(r'(?<!\u09b0)[\u200c\u200d](?!\u09cd\u09af)')
|
68 |
+
|
69 |
+
text = STANDARDIZE_ZW.sub('\u200D', text)
|
70 |
+
text = DELETE_ZW.sub('', text)
|
71 |
+
return text
|
72 |
+
|
73 |
+
def bn_unicode_normalise(batch):
|
74 |
+
_words = [bangla_normalizer(word)['normalized'] for word in get_text(batch).split()]
|
75 |
+
normalized_text = " ".join([word for word in _words if word is not None])
|
76 |
+
normalized_text = normalized_text.replace("\u2047", "-")
|
77 |
+
normalized_text = normalized_text.replace(u"\u098c", u"\u09ef")
|
78 |
+
normalized_text = unicodedata.normalize("NFC", normalized_text)
|
79 |
+
normalized_text = removeOptionalZW(normalized_text)
|
80 |
+
batch["norm_text"] = whisper_norm(normalized_text)
|
81 |
+
return batch
|
82 |
+
|
83 |
+
|
84 |
+
def data(dataset):
|
85 |
+
for item in dataset:
|
86 |
+
yield {**item["audio"], "reference": item["norm_text"]}
|
87 |
+
|
88 |
+
|
89 |
+
def main(args):
|
90 |
+
batch_size = args.batch_size
|
91 |
+
whisper_asr = pipeline(
|
92 |
+
"automatic-speech-recognition", model=args.model_id, device=args.device
|
93 |
+
)
|
94 |
+
|
95 |
+
whisper_asr.model.config.forced_decoder_ids = (
|
96 |
+
whisper_asr.tokenizer.get_decoder_prompt_ids(
|
97 |
+
language=args.language, task="transcribe"
|
98 |
+
)
|
99 |
+
)
|
100 |
+
|
101 |
+
dataset = load_dataset(
|
102 |
+
args.dataset,
|
103 |
+
args.config,
|
104 |
+
split=args.split,
|
105 |
+
streaming=args.streaming,
|
106 |
+
use_auth_token=True,
|
107 |
+
cache_dir=os.path.join(base_dir, 'datasets_cache'),
|
108 |
+
)
|
109 |
+
|
110 |
+
# Only uncomment for debugging
|
111 |
+
dataset = dataset.take(args.max_eval_samples)
|
112 |
+
|
113 |
+
dataset = dataset.cast_column("audio", Audio(sampling_rate=16000))
|
114 |
+
|
115 |
+
if args.do_bangla_unicode_normalize:
|
116 |
+
print("\n\n Doing Unicode Normalization! Make sure you have chosen the Bengali split of your dataset! \n\n")
|
117 |
+
dataset = dataset.map(bn_unicode_normalise)
|
118 |
+
else:
|
119 |
+
dataset = dataset.map(normalise)
|
120 |
+
|
121 |
+
dataset = dataset.filter(is_target_text_in_range, input_columns=["norm_text"])
|
122 |
+
|
123 |
+
predictions = []
|
124 |
+
references = []
|
125 |
+
|
126 |
+
# run streamed inference
|
127 |
+
for out in whisper_asr(data(dataset), batch_size=batch_size):
|
128 |
+
predictions.append(whisper_norm(out["text"]))
|
129 |
+
references.append(out["reference"][0])
|
130 |
+
|
131 |
+
wer = wer_metric.compute(references=references, predictions=predictions)
|
132 |
+
wer = round(100 * wer, 2)
|
133 |
+
|
134 |
+
cer = cer_metric.compute(references=references, predictions=predictions)
|
135 |
+
cer = round(100 * cer, 2)
|
136 |
+
|
137 |
+
print(f"\n\n WER: {wer} \n\n")
|
138 |
+
print(f"\n\n CER: {cer} \n\n")
|
139 |
+
|
140 |
+
evaluate.push_to_hub(
|
141 |
+
model_id=args.model_id,
|
142 |
+
metric_value=wer,
|
143 |
+
metric_type="wer",
|
144 |
+
metric_name="WER",
|
145 |
+
dataset_name=args.dataset,
|
146 |
+
dataset_type=args.dataset,
|
147 |
+
dataset_split=args.split,
|
148 |
+
dataset_config=args.config,
|
149 |
+
task_type="automatic-speech-recognition",
|
150 |
+
task_name="Automatic Speech Recognition",
|
151 |
+
overwrite=True
|
152 |
+
)
|
153 |
+
|
154 |
+
evaluate.push_to_hub(
|
155 |
+
model_id=args.model_id,
|
156 |
+
metric_value=cer,
|
157 |
+
metric_type="cer",
|
158 |
+
metric_name="CER",
|
159 |
+
dataset_name=args.dataset,
|
160 |
+
dataset_type=args.dataset,
|
161 |
+
dataset_split=args.split,
|
162 |
+
dataset_config=args.config,
|
163 |
+
task_type="automatic-speech-recognition",
|
164 |
+
task_name="Automatic Speech Recognition",
|
165 |
+
overwrite=True
|
166 |
+
)
|
167 |
+
|
168 |
+
|
169 |
+
|
170 |
+
if __name__ == "__main__":
|
171 |
+
parser = argparse.ArgumentParser()
|
172 |
+
|
173 |
+
parser.add_argument(
|
174 |
+
"--model_id",
|
175 |
+
type=str,
|
176 |
+
required=True,
|
177 |
+
help="Model identifier. Should be loadable with 🤗 Transformers",
|
178 |
+
)
|
179 |
+
parser.add_argument(
|
180 |
+
"--dataset",
|
181 |
+
type=str,
|
182 |
+
default="mozilla-foundation/common_voice_11_0",
|
183 |
+
help="Dataset name to evaluate the `model_id`. Should be loadable with 🤗 Datasets",
|
184 |
+
)
|
185 |
+
parser.add_argument(
|
186 |
+
"--config",
|
187 |
+
type=str,
|
188 |
+
required=True,
|
189 |
+
help="Config of the dataset. *E.g.* `'en'` for the English split of Common Voice",
|
190 |
+
)
|
191 |
+
parser.add_argument(
|
192 |
+
"--split",
|
193 |
+
type=str,
|
194 |
+
default="test",
|
195 |
+
help="Split of the dataset. *E.g.* `'test'`",
|
196 |
+
)
|
197 |
+
|
198 |
+
parser.add_argument(
|
199 |
+
"--device",
|
200 |
+
type=int,
|
201 |
+
default=-1,
|
202 |
+
help="The device to run the pipeline on. -1 for CPU (default), 0 for the first GPU and so on.",
|
203 |
+
)
|
204 |
+
parser.add_argument(
|
205 |
+
"--batch_size",
|
206 |
+
type=int,
|
207 |
+
default=16,
|
208 |
+
help="Number of samples to go through each streamed batch.",
|
209 |
+
)
|
210 |
+
parser.add_argument(
|
211 |
+
"--max_eval_samples",
|
212 |
+
type=int,
|
213 |
+
default=None,
|
214 |
+
help="Number of samples to be evaluated. Put a lower number e.g. 64 for testing this script.",
|
215 |
+
)
|
216 |
+
parser.add_argument(
|
217 |
+
"--streaming",
|
218 |
+
type=bool,
|
219 |
+
default=True,
|
220 |
+
help="Choose whether you'd like to download the entire dataset or stream it during the evaluation.",
|
221 |
+
)
|
222 |
+
parser.add_argument(
|
223 |
+
"--do_bangla_unicode_normalize",
|
224 |
+
type=bool,
|
225 |
+
default=True,
|
226 |
+
help="Choose whether you'd like to perform unicode normalization on your Bengali",
|
227 |
+
)
|
228 |
+
parser.add_argument(
|
229 |
+
"--language",
|
230 |
+
type=str,
|
231 |
+
required=True,
|
232 |
+
help="Two letter language code for the transcription language, e.g. use 'en' for English.",
|
233 |
+
)
|
234 |
+
|
235 |
+
args = parser.parse_args()
|
236 |
+
|
237 |
+
main(args)
|
my-training.py
ADDED
@@ -0,0 +1,767 @@
|
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|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
## Dependencies (run in the venv before running this script)
|
2 |
+
# pip install git+https://github.com/huggingface/datasets git+https://github.com/huggingface/transformers
|
3 |
+
# pip install huggingface_hub ipywidgets librosa evaluate>=0.3.0 jiwer bnunicodenormalizer
|
4 |
+
# pip install tensorboardX
|
5 |
+
# sudo add-apt-repository -y ppa:jonathonf/ffmpeg-4
|
6 |
+
# sudo apt update
|
7 |
+
# sudo apt install -y ffmpeg
|
8 |
+
#sudo apt-get install git-lfs
|
9 |
+
|
10 |
+
|
11 |
+
## Run the following commands separately before running the py version of this notebook to connect to HuggningFace Hub!
|
12 |
+
# git config --global credential.helper store
|
13 |
+
# huggingface-cli login
|
14 |
+
## Enter your token by visiting: https://huggingface.co/settings/tokens
|
15 |
+
## Create a repo in the hub:
|
16 |
+
# huggingface-cli repo create whisper-small-es OR, huggingface-cli repo create <repo_name/model_name>
|
17 |
+
## Install git lfs and clone the just created repo
|
18 |
+
# git lfs install
|
19 |
+
# git clone <repo_link>
|
20 |
+
## cd to the cloned repo and copy (cp) this python script or everything in training dir to that repo
|
21 |
+
# cd <repo_name/model_name>
|
22 |
+
# cp /home/mamun/asr_training/Govt_Speech_Demo/training/my-training.py .
|
23 |
+
|
24 |
+
|
25 |
+
#For more details: https://github.com/huggingface/community-events/tree/main/whisper-fine-tuning-event
|
26 |
+
|
27 |
+
|
28 |
+
|
29 |
+
## 1. Setting Up Environment Variables & Devices
|
30 |
+
import os
|
31 |
+
import torch
|
32 |
+
|
33 |
+
abs_path = os.path.abspath('.')
|
34 |
+
# base_dir = os.path.dirname(os.path.dirname(abs_path))
|
35 |
+
base_dir = os.path.dirname(abs_path)
|
36 |
+
|
37 |
+
os.environ['TRANSFORMERS_CACHE'] = os.path.join(base_dir, 'models_cache')
|
38 |
+
os.environ['TRANSFORMERS_OFFLINE'] = '0'
|
39 |
+
os.environ['HF_DATASETS_CACHE'] = os.path.join(base_dir, 'datasets_cache')
|
40 |
+
os.environ['HF_DATASETS_OFFLINE'] = '0'
|
41 |
+
|
42 |
+
# device = "GPU" if torch.cuda.is_available() else "CPU"
|
43 |
+
device = 'cuda' if torch.cuda.is_available() else 'cpu'
|
44 |
+
print(f"\n\n Device to be used: {device} \n\n")
|
45 |
+
|
46 |
+
|
47 |
+
## 2. Setting Up Variables
|
48 |
+
# model_name = "openai/whisper-tiny"
|
49 |
+
model_name = "openai/whisper-small"
|
50 |
+
# model_name = "openai/whisper-large-v2"
|
51 |
+
|
52 |
+
language = "Bengali"
|
53 |
+
task = "transcribe" # transcribe or translate
|
54 |
+
print(f"\n\n Loading {model_name} for {language} to {task}...this might take a while.. \n\n")
|
55 |
+
|
56 |
+
|
57 |
+
## 3. Setting Up Training Args
|
58 |
+
output_dir = "./"
|
59 |
+
overwrite_output_dir = True
|
60 |
+
max_steps = 50
|
61 |
+
# max_steps = 5
|
62 |
+
per_device_train_batch_size = 4
|
63 |
+
# per_device_train_batch_size = 1
|
64 |
+
per_device_eval_batch_size = 32
|
65 |
+
# per_device_eval_batch_size = 1
|
66 |
+
gradient_accumulation_steps = 16
|
67 |
+
# gradient_accumulation_steps = 1
|
68 |
+
dataloader_num_workers = 0 #Default: 0 and 0 for Windows
|
69 |
+
gradient_checkpointing = False
|
70 |
+
evaluation_strategy ="steps"
|
71 |
+
# eval_steps = 5
|
72 |
+
eval_steps = 100
|
73 |
+
save_strategy = "steps"
|
74 |
+
save_steps = 100
|
75 |
+
# save_steps = 5
|
76 |
+
save_total_limit = 5
|
77 |
+
learning_rate = 1e-5
|
78 |
+
lr_scheduler_type = "cosine" # "constant", "constant_with_warmup", "cosine", "cosine_with_restarts", "linear"(default), "polynomial", "inverse_sqrt"
|
79 |
+
warmup_steps = 1000 # (1 epoch)
|
80 |
+
# warmup_steps = 1
|
81 |
+
logging_steps = 25
|
82 |
+
# logging_steps = 1
|
83 |
+
# weight_decay = 0.01
|
84 |
+
weight_decay = 0
|
85 |
+
dropout = 0.1 # any value > 0.1 hurts performance. So, use values between 0.0 and 0.1
|
86 |
+
load_best_model_at_end = True
|
87 |
+
metric_for_best_model = "wer"
|
88 |
+
greater_is_better = False
|
89 |
+
bf16 = True
|
90 |
+
# bf16 = False
|
91 |
+
tf32 = True
|
92 |
+
# tf32 = False
|
93 |
+
generation_max_length = 448 # ensure that the generation_max_length is equal to model_max_length. model_max_length = 1024 for whisper-small (see tokenizer config.json) also make model.config.max_length = 1024
|
94 |
+
report_to = ["tensorboard"]
|
95 |
+
predict_with_generate = True
|
96 |
+
push_to_hub = True
|
97 |
+
# push_to_hub = False
|
98 |
+
freeze_feature_encoder = False
|
99 |
+
early_stopping_patience = 10
|
100 |
+
apply_spec_augment = True
|
101 |
+
torch_compile = False #Windows not yet supported
|
102 |
+
optim="adamw_hf" # adamw_hf (default), adamw_torch, adamw_torch_fused (improved), adamw_apex_fused, adamw_anyprecision or adafactor
|
103 |
+
|
104 |
+
|
105 |
+
## 4. Load Datasets
|
106 |
+
print("\n\n Loading Datasets...this might take a while..\n\n")
|
107 |
+
|
108 |
+
from datasets import load_dataset, DatasetDict, Features, Value, Audio
|
109 |
+
|
110 |
+
common_voice = DatasetDict()
|
111 |
+
google_fleurs = DatasetDict()
|
112 |
+
openslr = DatasetDict()
|
113 |
+
## commonvoice_11.0 + google_fleurs + openslr53
|
114 |
+
my_dataset = DatasetDict()
|
115 |
+
|
116 |
+
common_voice["train"] = load_dataset("mozilla-foundation/common_voice_11_0", "bn", split="train+validation", cache_dir=os.path.join(base_dir, 'datasets_cache'))
|
117 |
+
google_fleurs["train"] = load_dataset("google/fleurs", "bn_in", split="train+validation", cache_dir=os.path.join(base_dir, 'datasets_cache'))
|
118 |
+
openslr = load_dataset("openslr", "SLR53", cache_dir=os.path.join(base_dir, 'datasets_cache'))
|
119 |
+
|
120 |
+
# loading crblp dataset
|
121 |
+
features = Features(
|
122 |
+
{
|
123 |
+
"text": Value("string"),
|
124 |
+
'path': Value('string'),
|
125 |
+
"audio": Audio(sampling_rate=16000)
|
126 |
+
}
|
127 |
+
)
|
128 |
+
|
129 |
+
crblp = load_dataset(
|
130 |
+
'csv',
|
131 |
+
data_files='D:/Govt_Speech_Demo/crblp_speech_corpus/crblp_train.csv',
|
132 |
+
split='train',
|
133 |
+
cache_dir=os.path.join(base_dir, 'datasets_cache'),
|
134 |
+
features=features
|
135 |
+
)
|
136 |
+
|
137 |
+
|
138 |
+
common_voice["test"] = load_dataset("mozilla-foundation/common_voice_11_0", "bn", split="test", cache_dir=os.path.join(base_dir, 'datasets_cache'))
|
139 |
+
google_fleurs["test"] = load_dataset("google/fleurs", "bn_in", split="test", cache_dir=os.path.join(base_dir, 'datasets_cache'))
|
140 |
+
|
141 |
+
|
142 |
+
# see count of samples in each dataset
|
143 |
+
print("\n\n Datasets Loaded \n\n")
|
144 |
+
print(common_voice)
|
145 |
+
print(google_fleurs)
|
146 |
+
print(openslr)
|
147 |
+
print(crblp)
|
148 |
+
|
149 |
+
|
150 |
+
## 5. Small Subset for Testing
|
151 |
+
# common_voice['train'] = common_voice['train'].select(range(50))
|
152 |
+
# common_voice['test'] = common_voice['test'].select(range(50))
|
153 |
+
# google_fleurs['train'] = google_fleurs['train'].select(range(50))
|
154 |
+
# google_fleurs['test'] = google_fleurs['test'].select(range(50))
|
155 |
+
# openslr['train'] = openslr['train'].select(range(50))
|
156 |
+
# crblp = crblp.select(range(50))
|
157 |
+
|
158 |
+
# print("\n\n For testing, the small subsets are:")
|
159 |
+
# print(common_voice)
|
160 |
+
# print(google_fleurs)
|
161 |
+
# print(openslr)
|
162 |
+
# print(crblp)
|
163 |
+
# print("\n")
|
164 |
+
|
165 |
+
# print("\n EXITING \n")
|
166 |
+
# import sys
|
167 |
+
# sys.exit()
|
168 |
+
|
169 |
+
|
170 |
+
## Removing bad samples from common_voice based on upvotes and downvotes
|
171 |
+
print("\n BEFORE Filtering by Upvotes (Common Voice): \n")
|
172 |
+
print(common_voice["train"])
|
173 |
+
# FILTERING!!! Will get 37k Data if >0 and will get 201k Data if >=0 out of 207k
|
174 |
+
common_voice["train"] = common_voice["train"].filter(lambda x: (x["up_votes"] - x["down_votes"]) >= 0, num_proc=None)
|
175 |
+
print("\n AFTER Filtering by Upvotes (Common Voice): \n")
|
176 |
+
print(common_voice["train"])
|
177 |
+
|
178 |
+
|
179 |
+
## REMOVE Corrupt Files (Only required if you use the "other" split of Common Voice)
|
180 |
+
# skipFiles = open("corrupt_files.txt").read().splitlines()
|
181 |
+
# skipFiles = skipFiles[3:]
|
182 |
+
# length = len(skipFiles)
|
183 |
+
# first = skipFiles[0]
|
184 |
+
# last = skipFiles[-1]
|
185 |
+
# print(f"\n No. of corrupt files: {length}, First: {first}, Last {last}\n")
|
186 |
+
|
187 |
+
# print("\n Finding indexes of corrupt files... \n")
|
188 |
+
# from tqdm import tqdm
|
189 |
+
# count=0
|
190 |
+
# error_index = []
|
191 |
+
# for i in tqdm(range(len(common_voice["train"]))):
|
192 |
+
# path = common_voice["train"][i]["path"].split("/")[-1].split(".")[0]
|
193 |
+
# if path in skipFiles:
|
194 |
+
# # print(path)
|
195 |
+
# count+=1
|
196 |
+
# error_index.append(i)
|
197 |
+
# print(f"\n Total Corrupt Files: {count} \n")
|
198 |
+
|
199 |
+
# print("\n Removing corrupt files from the Common Voice dataset...\n")
|
200 |
+
# common_voice["train"] = common_voice["train"].filter(lambda example, idx: idx not in error_index, with_indices=True)
|
201 |
+
|
202 |
+
|
203 |
+
print("\n\n So, the datasets to be trained are: \n\n")
|
204 |
+
print("\n Common Voice 11.0 - Bangla\n")
|
205 |
+
print(common_voice)
|
206 |
+
print("\n Google Fleurs - Bangla \n")
|
207 |
+
print(google_fleurs)
|
208 |
+
print("\n OpenSLR-53 - Bangla \n")
|
209 |
+
print(openslr)
|
210 |
+
print("\n CRBLP - Bangla \n")
|
211 |
+
print(crblp)
|
212 |
+
print("\n")
|
213 |
+
|
214 |
+
|
215 |
+
|
216 |
+
## 6. Merge Datasets
|
217 |
+
from datasets import concatenate_datasets, Audio
|
218 |
+
|
219 |
+
sampling_rate = 16000
|
220 |
+
|
221 |
+
## resample to specified sampling rate
|
222 |
+
common_voice = common_voice.cast_column("audio", Audio(sampling_rate))
|
223 |
+
google_fleurs = google_fleurs.cast_column("audio", Audio(sampling_rate))
|
224 |
+
openslr = openslr.cast_column("audio", Audio(sampling_rate))
|
225 |
+
crblp = crblp.cast_column("audio", Audio(sampling_rate))
|
226 |
+
|
227 |
+
## normalise columns to ["audio", "sentence"]
|
228 |
+
common_voice = common_voice.remove_columns(
|
229 |
+
set(common_voice['test'].features.keys()) - {"audio", "sentence"}
|
230 |
+
)
|
231 |
+
|
232 |
+
google_fleurs = google_fleurs.rename_column("raw_transcription", "sentence")
|
233 |
+
google_fleurs = google_fleurs.remove_columns(
|
234 |
+
set(google_fleurs['test'].features.keys()) - {"audio", "sentence"}
|
235 |
+
)
|
236 |
+
|
237 |
+
openslr = openslr.remove_columns(
|
238 |
+
set(openslr['train'].features.keys()) - {"audio", "sentence"}
|
239 |
+
)
|
240 |
+
|
241 |
+
crblp = crblp.rename_column("text", "sentence")
|
242 |
+
crblp = crblp.remove_columns(
|
243 |
+
set(crblp.features.keys()) - {"audio", "sentence"}
|
244 |
+
)
|
245 |
+
|
246 |
+
## check if all audio are in float32 dtype or not.
|
247 |
+
## a fix is: https://github.com/huggingface/datasets/issues/5345
|
248 |
+
print("\n Checking all audio dtype is float32 or not... \n")
|
249 |
+
print(f'Common Voice Train: {common_voice["train"][0]["audio"]["array"].dtype}')
|
250 |
+
print(f'Common Voice Test: {common_voice["test"][0]["audio"]["array"].dtype}')
|
251 |
+
print(f'Google Fleurs Train: {google_fleurs["train"][0]["audio"]["array"].dtype}')
|
252 |
+
print(f'Google Fleurs Test: {google_fleurs["test"][0]["audio"]["array"].dtype}')
|
253 |
+
print(f'OpenSlR: {openslr["train"][0]["audio"]["array"].dtype}')
|
254 |
+
print(f'CRBLP: {crblp[0]["audio"]["array"].dtype}')
|
255 |
+
print("\n")
|
256 |
+
|
257 |
+
|
258 |
+
## merge the three datasets
|
259 |
+
# my_dataset['train'] = concatenate_datasets([common_voice['train'], google_fleurs['train'], openslr['train']]) #for linux
|
260 |
+
my_dataset['train'] = concatenate_datasets([common_voice['train'], google_fleurs['train'], openslr['train'], crblp]) #for linux
|
261 |
+
# my_dataset['train'] = concatenate_datasets([common_voice['train'], openslr['train']])
|
262 |
+
# my_dataset['train'] = concatenate_datasets([google_fleurs['train'], openslr['train']]) #for windows no commonvoice as it requires ffmpeg-4
|
263 |
+
# my_dataset['train'] = google_fleurs['train']
|
264 |
+
my_dataset['test'] = concatenate_datasets([common_voice['test'], google_fleurs['test']]) #for linux
|
265 |
+
# my_dataset['test'] = common_voice['test']
|
266 |
+
# my_dataset['test'] = concatenate_datasets([google_fleurs['test']]) #for windows no commonvoice as it requires ffmpeg-4
|
267 |
+
|
268 |
+
#shuffle train set with seed=42
|
269 |
+
my_dataset['train'] = my_dataset['train'].shuffle(seed=10)
|
270 |
+
|
271 |
+
print("\n\n AFTER MERGING, train and validation sets are: ")
|
272 |
+
print(my_dataset)
|
273 |
+
print("\n")
|
274 |
+
|
275 |
+
|
276 |
+
## 6. Augmentation
|
277 |
+
print("\n\n Augmenting Datasets...this might take a while..\n\n")
|
278 |
+
from audiomentations import (
|
279 |
+
AddBackgroundNoise,
|
280 |
+
AddGaussianNoise,
|
281 |
+
Compose,
|
282 |
+
Gain,
|
283 |
+
OneOf,
|
284 |
+
PitchShift,
|
285 |
+
PolarityInversion,
|
286 |
+
TimeStretch,
|
287 |
+
)
|
288 |
+
|
289 |
+
# define augmentation
|
290 |
+
augmentation = Compose(
|
291 |
+
[
|
292 |
+
TimeStretch(min_rate=0.9, max_rate=1.1, p=0.2, leave_length_unchanged=False),
|
293 |
+
Gain(min_gain_in_db=-6, max_gain_in_db=6, p=0.1),
|
294 |
+
PitchShift(min_semitones=-4, max_semitones=4, p=0.2),
|
295 |
+
AddGaussianNoise(min_amplitude=0.005, max_amplitude=0.015, p=1.0),
|
296 |
+
]
|
297 |
+
)
|
298 |
+
|
299 |
+
def augment_dataset(batch):
|
300 |
+
# load and (possibly) resample audio data to 16kHz
|
301 |
+
sample = batch['audio']
|
302 |
+
|
303 |
+
# apply augmentation
|
304 |
+
augmented_waveform = augmentation(sample["array"], sample_rate=sample["sampling_rate"])
|
305 |
+
batch['audio']["array"] = augmented_waveform
|
306 |
+
return batch
|
307 |
+
|
308 |
+
# augment training data
|
309 |
+
augmented_raw_training_dataset = my_dataset["train"].map(
|
310 |
+
augment_dataset,
|
311 |
+
num_proc=1,
|
312 |
+
desc="augment train dataset",
|
313 |
+
load_from_cache_file=True,
|
314 |
+
cache_file_name=os.path.join(base_dir, 'datasets_cache', 'augmented_train_cache.arrow')
|
315 |
+
)
|
316 |
+
|
317 |
+
print("\n COMBINING Augmented Dataset with Normal Dataset..... \n")
|
318 |
+
# combine
|
319 |
+
my_dataset["train"] = concatenate_datasets([my_dataset["train"], augmented_raw_training_dataset])
|
320 |
+
my_dataset["train"] = my_dataset["train"].shuffle(seed=42)
|
321 |
+
|
322 |
+
|
323 |
+
my_dataset["train"] = my_dataset["train"].select(range(2500))
|
324 |
+
my_dataset["test"] = my_dataset["test"].select(range(50))
|
325 |
+
|
326 |
+
print("\n\n AFTER AUGMENTATION, FINAL train and validation sets are: ")
|
327 |
+
print("\n FINAL DATASET: \n")
|
328 |
+
print(my_dataset)
|
329 |
+
|
330 |
+
# #debugging
|
331 |
+
# print("\n EXITING \n")
|
332 |
+
# import sys
|
333 |
+
# sys.exit()
|
334 |
+
|
335 |
+
## 7. Prepare Feature Extractor, Tokenizer and Processor
|
336 |
+
from transformers import WhisperFeatureExtractor, WhisperTokenizer, WhisperTokenizerFast, WhisperProcessor
|
337 |
+
|
338 |
+
feature_extractor = WhisperFeatureExtractor.from_pretrained(model_name)
|
339 |
+
|
340 |
+
# tokenizer = WhisperTokenizer.from_pretrained(model_name, language=language, task=task)
|
341 |
+
# tokenizer = WhisperTokenizerFast.from_pretrained(model_name, language=language, task=task)
|
342 |
+
|
343 |
+
processor = WhisperProcessor.from_pretrained(model_name, language=language, task=task)
|
344 |
+
|
345 |
+
|
346 |
+
## 8. Preprocessing Data
|
347 |
+
print("\n\n Preprocessing Datasets...this might take a while..\n\n")
|
348 |
+
|
349 |
+
from transformers.models.whisper.english_normalizer import BasicTextNormalizer
|
350 |
+
from bnunicodenormalizer import Normalizer
|
351 |
+
import unicodedata
|
352 |
+
import re
|
353 |
+
|
354 |
+
do_lower_case = False
|
355 |
+
do_remove_punctuation = False
|
356 |
+
do_bangla_unicode_normalization = True
|
357 |
+
|
358 |
+
normalizer = BasicTextNormalizer()
|
359 |
+
bangla_normalizer = Normalizer(allow_english=True)
|
360 |
+
|
361 |
+
|
362 |
+
def removeOptionalZW(text):
|
363 |
+
"""
|
364 |
+
Removes all optional occurrences of ZWNJ or ZWJ from Bangla text.
|
365 |
+
"""
|
366 |
+
# Regex for matching zero witdh joiner variations.
|
367 |
+
STANDARDIZE_ZW = re.compile(r'(?<=\u09b0)[\u200c\u200d]+(?=\u09cd\u09af)')
|
368 |
+
|
369 |
+
# Regex for removing standardized zero width joiner, except in edge cases.
|
370 |
+
DELETE_ZW = re.compile(r'(?<!\u09b0)[\u200c\u200d](?!\u09cd\u09af)')
|
371 |
+
|
372 |
+
text = STANDARDIZE_ZW.sub('\u200D', text)
|
373 |
+
text = DELETE_ZW.sub('', text)
|
374 |
+
return text
|
375 |
+
|
376 |
+
|
377 |
+
def prepare_dataset(batch):
|
378 |
+
# load and (possibly) resample audio data to 16kHz
|
379 |
+
audio = batch["audio"]
|
380 |
+
|
381 |
+
# compute log-Mel input features from input audio array
|
382 |
+
inputs = processor.feature_extractor(
|
383 |
+
audio["array"],
|
384 |
+
sampling_rate=audio["sampling_rate"],
|
385 |
+
return_attention_mask=apply_spec_augment,
|
386 |
+
)
|
387 |
+
batch["input_features"] = inputs.input_features[0]
|
388 |
+
|
389 |
+
# compute input length
|
390 |
+
batch["input_length"] = len(batch["audio"])
|
391 |
+
# batch["input_length"] = len(batch["input_features"])
|
392 |
+
|
393 |
+
# if spec augmentation applied, get attention_mask to guide the mask along time axis
|
394 |
+
if apply_spec_augment:
|
395 |
+
batch["attention_mask"] = inputs.get("attention_mask")[0]
|
396 |
+
|
397 |
+
|
398 |
+
# optional pre-processing steps
|
399 |
+
transcription = batch["sentence"]
|
400 |
+
if do_lower_case:
|
401 |
+
transcription = transcription.lower()
|
402 |
+
if do_remove_punctuation:
|
403 |
+
transcription = normalizer(transcription).strip()
|
404 |
+
if do_bangla_unicode_normalization:
|
405 |
+
_words = [bangla_normalizer(word)['normalized'] for word in transcription.split()]
|
406 |
+
transcription = " ".join([word for word in _words if word is not None])
|
407 |
+
transcription = transcription.replace("\u2047", "-")
|
408 |
+
transcription = transcription.replace(u"\u098c", u"\u09ef")
|
409 |
+
transcription = unicodedata.normalize("NFC", transcription)
|
410 |
+
transcription = removeOptionalZW(transcription)
|
411 |
+
|
412 |
+
# encode target text to label ids
|
413 |
+
batch["labels"] = processor.tokenizer(transcription).input_ids
|
414 |
+
|
415 |
+
# compute labels length **with** special tokens! -> total label length
|
416 |
+
batch["labels_length"] = len(batch["labels"])
|
417 |
+
|
418 |
+
return batch
|
419 |
+
|
420 |
+
## my_dataset is DatasetDict dictionary whereas my_dataset["train"] is Dataset Object.
|
421 |
+
## map function parameters for both are different!
|
422 |
+
## see: https://github.com/huggingface/datasets/issues/2407
|
423 |
+
|
424 |
+
## This,
|
425 |
+
my_dataset = my_dataset.map(prepare_dataset,
|
426 |
+
num_proc=1, # if num_proc>1, then mapping might get stuck. use num_proc=1 in that case.
|
427 |
+
load_from_cache_file=True,
|
428 |
+
cache_file_names={
|
429 |
+
"train" : os.path.join(base_dir, 'datasets_cache', 'lol_preprocessed_train_cache.arrow'),
|
430 |
+
"test" : os.path.join(base_dir, 'datasets_cache', 'lol_preprocessed_test_cache.arrow'),
|
431 |
+
}
|
432 |
+
)
|
433 |
+
## OR this,
|
434 |
+
# my_dataset["train"] = my_dataset["train"].map(
|
435 |
+
# prepare_dataset,
|
436 |
+
# num_proc=4, # if num_proc>1, then mapping might get stuck. use num_proc=1 in that case.
|
437 |
+
# load_from_cache_file=True,
|
438 |
+
# cache_file_name=os.path.join(base_dir, 'datasets_cache', 'preprocessed_train_cache.arrow')
|
439 |
+
# )
|
440 |
+
|
441 |
+
# my_dataset["test"] = my_dataset["test"].map(
|
442 |
+
# prepare_dataset,
|
443 |
+
# num_proc=4, # if num_proc>1, then mapping might get stuck. use num_proc=1 in that case.
|
444 |
+
# load_from_cache_file=True,
|
445 |
+
# cache_file_name=os.path.join(base_dir, 'datasets_cache', 'preprocessed_test_cache.arrow')
|
446 |
+
# )
|
447 |
+
|
448 |
+
|
449 |
+
print("\n\n AFTER PREPROCESSING, final train and validation sets are: ")
|
450 |
+
print(my_dataset)
|
451 |
+
print("\n")
|
452 |
+
|
453 |
+
## 9. Filter too Short or too Long Audio Files
|
454 |
+
MAX_DURATION_IN_SECONDS = 30.0
|
455 |
+
max_input_length = MAX_DURATION_IN_SECONDS * 16000
|
456 |
+
|
457 |
+
def filter_inputs(input_length):
|
458 |
+
"""Filter inputs with zero input length or longer than 30s"""
|
459 |
+
return 0 < input_length < max_input_length
|
460 |
+
|
461 |
+
my_dataset = my_dataset.filter(filter_inputs, input_columns=["input_length"])
|
462 |
+
|
463 |
+
# my_dataset["train"] = my_dataset["train"].filter(
|
464 |
+
# filter_inputs,
|
465 |
+
# input_columns=["input_length"],
|
466 |
+
# )
|
467 |
+
# my_dataset["test"] = my_dataset["test"].filter(
|
468 |
+
# filter_inputs,
|
469 |
+
# input_columns=["input_length"],
|
470 |
+
# )
|
471 |
+
|
472 |
+
print("\n\n AFTER FILTERING INPUTS, final train and validation sets are: ")
|
473 |
+
print(my_dataset)
|
474 |
+
print("\n")
|
475 |
+
|
476 |
+
max_label_length = generation_max_length #(max_label_length should be equal to generation_max_length)
|
477 |
+
|
478 |
+
def filter_labels(labels_length):
|
479 |
+
"""Filter label sequences longer than max length (448)"""
|
480 |
+
return labels_length < max_label_length
|
481 |
+
|
482 |
+
my_dataset = my_dataset.filter(filter_labels, input_columns=["labels_length"])
|
483 |
+
|
484 |
+
# my_dataset["train"] = my_dataset["train"].filter(
|
485 |
+
# filter_labels,
|
486 |
+
# input_columns=["labels_length"],
|
487 |
+
# )
|
488 |
+
|
489 |
+
# my_dataset["test"] = my_dataset["test"].filter(
|
490 |
+
# filter_labels,
|
491 |
+
# input_columns=["labels_length"],
|
492 |
+
# )
|
493 |
+
|
494 |
+
print("\n\n AFTER FILTERING LABELS, final train and validation sets are: ")
|
495 |
+
print(my_dataset)
|
496 |
+
print("\n")
|
497 |
+
|
498 |
+
|
499 |
+
import re
|
500 |
+
def filter_transcripts(transcript):
|
501 |
+
"""Filter transcripts with empty strings and samples containing English characters & numbers"""
|
502 |
+
pattern = r'^.*[a-zA-Z0-9]+.*$'
|
503 |
+
match = re.match(pattern, transcript)
|
504 |
+
return len(transcript.split(" ")) > 1 and not bool(match)
|
505 |
+
|
506 |
+
my_dataset = my_dataset.filter(filter_transcripts, input_columns=["sentence"])
|
507 |
+
|
508 |
+
# my_dataset["train"] = my_dataset["train"].filter(
|
509 |
+
# filter_transcripts,
|
510 |
+
# input_columns=["sentence"],
|
511 |
+
# )
|
512 |
+
# my_dataset["test"] = my_dataset["test"].filter(
|
513 |
+
# filter_transcripts,
|
514 |
+
# input_columns=["sentence"],
|
515 |
+
# )
|
516 |
+
|
517 |
+
print("\n\n AFTER FILTERING TRANSCRIPTS, final train and validation sets are: ")
|
518 |
+
print("\n My FINAL DATASET \n")
|
519 |
+
print(my_dataset)
|
520 |
+
print("\n")
|
521 |
+
|
522 |
+
|
523 |
+
## 10. Save & Cleanup Cache Files (DON'T save too large datasets..will take up all space!!)
|
524 |
+
## Only save, if you want it to export it to another PC!!
|
525 |
+
## Else, map function stores the cache files via cache_file_name parameter!!
|
526 |
+
|
527 |
+
# print("\n\n Saving Preprocessed Dataset to Disk..\n\n")
|
528 |
+
|
529 |
+
# my_dataset.save_to_disk(os.path.join(base_dir, "datasets_cache"))
|
530 |
+
|
531 |
+
## Removes unused cached files & returns the number of removed cache files
|
532 |
+
print("\n Removing UNUSED Cache Files: \n")
|
533 |
+
try:
|
534 |
+
print(f"{common_voice.cleanup_cache_files()} for common_voice")
|
535 |
+
print(f"{google_fleurs.cleanup_cache_files()} for google_fleurs")
|
536 |
+
print(f"{openslr.cleanup_cache_files()} for openslr")
|
537 |
+
print(f"{crblp.cleanup_cache_files()} for crblp")
|
538 |
+
print(f"{my_dataset.cleanup_cache_files()} for my_dataset")
|
539 |
+
|
540 |
+
except Exception as e:
|
541 |
+
print(f"\n\n UNABLE to REMOVE some Cache files. \n Error: {e} \n\n")
|
542 |
+
|
543 |
+
|
544 |
+
## 11. Load Already Preprocessed Dataset from Disk
|
545 |
+
## Only load if you have a saved dataset via save_to_disk method!!
|
546 |
+
## Do Once 4 to 6 and 8 to 10. Then start from 7 and 11. EVERYTIME!!!
|
547 |
+
|
548 |
+
# from datasets import load_from_disk
|
549 |
+
# print("\n\n Loading Preprocessed Dataset from Disk..\n\n")
|
550 |
+
|
551 |
+
# my_dataset = load_from_disk(os.path.join(base_dir, "datasets_cache"))
|
552 |
+
|
553 |
+
|
554 |
+
## 12. Define Data Collator
|
555 |
+
import torch
|
556 |
+
from dataclasses import dataclass
|
557 |
+
from typing import Any, Dict, List, Union
|
558 |
+
|
559 |
+
@dataclass
|
560 |
+
class DataCollatorSpeechSeq2SeqWithPadding:
|
561 |
+
processor: Any
|
562 |
+
forward_attention_mask: bool
|
563 |
+
|
564 |
+
def __call__(self, features: List[Dict[str, Union[List[int], torch.Tensor]]]) -> Dict[str, torch.Tensor]:
|
565 |
+
# split inputs and labels since they have to be of different lengths and need different padding methods
|
566 |
+
# first treat the audio inputs by simply returning torch tensors
|
567 |
+
input_features = [{"input_features": feature["input_features"]} for feature in features]
|
568 |
+
batch = self.processor.feature_extractor.pad(input_features, return_tensors="pt")
|
569 |
+
|
570 |
+
if self.forward_attention_mask:
|
571 |
+
batch["attention_mask"] = torch.LongTensor([feature["attention_mask"] for feature in features])
|
572 |
+
|
573 |
+
# get the tokenized label sequences
|
574 |
+
label_features = [{"input_ids": feature["labels"]} for feature in features]
|
575 |
+
# pad the labels to max length
|
576 |
+
labels_batch = self.processor.tokenizer.pad(label_features, return_tensors="pt")
|
577 |
+
|
578 |
+
# replace padding with -100 to ignore loss correctly
|
579 |
+
labels = labels_batch["input_ids"].masked_fill(labels_batch.attention_mask.ne(1), -100)
|
580 |
+
|
581 |
+
# if bos token is appended in previous tokenization step,
|
582 |
+
# cut bos token here as it's append later anyways
|
583 |
+
if (labels[:, 0] == self.processor.tokenizer.bos_token_id).all().cpu().item():
|
584 |
+
labels = labels[:, 1:]
|
585 |
+
|
586 |
+
batch["labels"] = labels
|
587 |
+
|
588 |
+
return batch
|
589 |
+
|
590 |
+
|
591 |
+
|
592 |
+
data_collator = DataCollatorSpeechSeq2SeqWithPadding(processor=processor, forward_attention_mask=apply_spec_augment)
|
593 |
+
|
594 |
+
|
595 |
+
|
596 |
+
## 13. Define Evaluation Metrics
|
597 |
+
import evaluate
|
598 |
+
|
599 |
+
wer_metric = evaluate.load("wer", cache_dir=os.path.join(base_dir, "metrics_cache"))
|
600 |
+
cer_metric = evaluate.load("cer", cache_dir=os.path.join(base_dir, "metrics_cache"))
|
601 |
+
|
602 |
+
do_normalize_eval = True
|
603 |
+
|
604 |
+
def compute_metrics(pred):
|
605 |
+
pred_ids = pred.predictions
|
606 |
+
label_ids = pred.label_ids
|
607 |
+
|
608 |
+
# replace -100 with the pad_token_id
|
609 |
+
label_ids[label_ids == -100] = processor.tokenizer.pad_token_id
|
610 |
+
|
611 |
+
# we do not want to group tokens when computing the metrics
|
612 |
+
pred_str = processor.tokenizer.batch_decode(pred_ids, skip_special_tokens=True)
|
613 |
+
label_str = processor.tokenizer.batch_decode(label_ids, skip_special_tokens=True)
|
614 |
+
|
615 |
+
if do_normalize_eval:
|
616 |
+
pred_str = [normalizer(pred) for pred in pred_str]
|
617 |
+
label_str = [normalizer(label) for label in label_str]
|
618 |
+
|
619 |
+
wer = 100 * wer_metric.compute(predictions=pred_str, references=label_str)
|
620 |
+
cer = 100 * cer_metric.compute(predictions=pred_str, references=label_str)
|
621 |
+
|
622 |
+
return {"cer": cer, "wer": wer}
|
623 |
+
|
624 |
+
|
625 |
+
## 14. Load a Pre-Trained Checkpoint
|
626 |
+
print("\n\n Loading Model to Device..\n\n")
|
627 |
+
|
628 |
+
from transformers import WhisperForConditionalGeneration
|
629 |
+
|
630 |
+
model = WhisperForConditionalGeneration.from_pretrained(model_name)
|
631 |
+
model = model.to(device)
|
632 |
+
|
633 |
+
|
634 |
+
## 15. Override generation arguments
|
635 |
+
model.config.apply_spec_augment = apply_spec_augment
|
636 |
+
model.config.max_length = generation_max_length
|
637 |
+
model.config.dropout = dropout
|
638 |
+
model.config.forced_decoder_ids = None
|
639 |
+
model.config.suppress_tokens = []
|
640 |
+
if gradient_checkpointing:
|
641 |
+
model.config.use_cache = False
|
642 |
+
if freeze_feature_encoder:
|
643 |
+
model.freeze_feature_encoder()
|
644 |
+
|
645 |
+
model.generation_config.max_length = generation_max_length
|
646 |
+
model.generation_config.max_new_tokens = generation_max_length
|
647 |
+
|
648 |
+
## 16. Define the Training Configuration
|
649 |
+
from transformers import Seq2SeqTrainingArguments
|
650 |
+
|
651 |
+
training_args = Seq2SeqTrainingArguments(
|
652 |
+
output_dir=output_dir,
|
653 |
+
overwrite_output_dir=overwrite_output_dir,
|
654 |
+
max_steps=max_steps,
|
655 |
+
per_device_train_batch_size=per_device_train_batch_size,
|
656 |
+
per_device_eval_batch_size=per_device_eval_batch_size,
|
657 |
+
gradient_accumulation_steps=gradient_accumulation_steps,
|
658 |
+
gradient_checkpointing=gradient_checkpointing,
|
659 |
+
dataloader_num_workers=dataloader_num_workers,
|
660 |
+
evaluation_strategy=evaluation_strategy,
|
661 |
+
eval_steps=eval_steps,
|
662 |
+
save_strategy=save_strategy,
|
663 |
+
save_steps=save_steps,
|
664 |
+
save_total_limit=save_total_limit,
|
665 |
+
learning_rate=learning_rate,
|
666 |
+
lr_scheduler_type=lr_scheduler_type,
|
667 |
+
warmup_steps=warmup_steps,
|
668 |
+
logging_steps=logging_steps,
|
669 |
+
weight_decay=weight_decay,
|
670 |
+
load_best_model_at_end=load_best_model_at_end,
|
671 |
+
metric_for_best_model=metric_for_best_model,
|
672 |
+
greater_is_better=greater_is_better,
|
673 |
+
bf16=bf16,
|
674 |
+
tf32=tf32,
|
675 |
+
torch_compile=torch_compile,
|
676 |
+
optim=optim,
|
677 |
+
generation_max_length=generation_max_length,
|
678 |
+
report_to=report_to,
|
679 |
+
predict_with_generate=predict_with_generate,
|
680 |
+
push_to_hub=push_to_hub,
|
681 |
+
)
|
682 |
+
|
683 |
+
from transformers import Seq2SeqTrainer
|
684 |
+
import transformers as tf
|
685 |
+
|
686 |
+
trainer = Seq2SeqTrainer(
|
687 |
+
args=training_args,
|
688 |
+
model=model,
|
689 |
+
train_dataset=my_dataset["train"],
|
690 |
+
eval_dataset=my_dataset["test"],
|
691 |
+
data_collator=data_collator,
|
692 |
+
compute_metrics=compute_metrics,
|
693 |
+
tokenizer=processor.feature_extractor,
|
694 |
+
callbacks=[tf.EarlyStoppingCallback(early_stopping_patience=early_stopping_patience)],
|
695 |
+
)
|
696 |
+
|
697 |
+
## We'll save the processor object once before starting training. Since the processor is not trainable, it won't change over the course of training.
|
698 |
+
## The checkpoint dirs don't save the processor files:
|
699 |
+
## (added_tokens.json, merges.txt, normalizer.json, special_tokens_map.json, tokenizer_config.json, vocab.json)
|
700 |
+
## So, we save beforehand the processor in the best_model directory.
|
701 |
+
## This is done so that if we stop training earlier than expected,
|
702 |
+
## then we can copy the above files from the best_model dir to the checkpoint folder
|
703 |
+
## to load the processor and run the model from the checkpoint dir.
|
704 |
+
|
705 |
+
# No need to create best_model folder as trainer automatically creates it!
|
706 |
+
# if not os.path.exists("best_model"):
|
707 |
+
# os.makedirs("best_model")
|
708 |
+
processor.save_pretrained("best_model")
|
709 |
+
|
710 |
+
|
711 |
+
## 17. Training
|
712 |
+
print("\n\n Training STARTED..\n\n")
|
713 |
+
|
714 |
+
train_result = trainer.train()
|
715 |
+
|
716 |
+
## resume from the latest checkpoint
|
717 |
+
# train_result = trainer.train(resume_from_checkpoint=True)
|
718 |
+
|
719 |
+
## resume training from the specific checkpoint in the directory passed
|
720 |
+
# train_result = trainer.train(resume_from_checkpoint="checkpoint-4000")
|
721 |
+
|
722 |
+
print("\n\n Training COMPLETED...\n\n")
|
723 |
+
|
724 |
+
|
725 |
+
## 18. Evaluating & Saving Metrics & Model
|
726 |
+
print("\n\n Evaluating Model & Saving Metrics...\n\n")
|
727 |
+
|
728 |
+
processor.save_pretrained(save_directory=output_dir)
|
729 |
+
# trainer.save_model()
|
730 |
+
|
731 |
+
metrics = train_result.metrics
|
732 |
+
trainer.save_metrics("train", metrics)
|
733 |
+
trainer.save_state()
|
734 |
+
|
735 |
+
metrics = trainer.evaluate(
|
736 |
+
metric_key_prefix="eval",
|
737 |
+
max_length=training_args.generation_max_length,
|
738 |
+
num_beams=training_args.generation_num_beams,
|
739 |
+
)
|
740 |
+
|
741 |
+
trainer.save_metrics("eval", metrics)
|
742 |
+
|
743 |
+
|
744 |
+
## 19. Push to Hub
|
745 |
+
if push_to_hub:
|
746 |
+
print("\n\n Pushing to Hub...\n\n")
|
747 |
+
|
748 |
+
trainer.create_model_card()
|
749 |
+
# kwargs = {
|
750 |
+
# # "dataset_tags": ["mozilla-foundation/common_voice_11_0", "google/fleurs", "openslr"],
|
751 |
+
# "dataset_tags": ["mozilla-foundation/common_voice_11_0", "google/fleurs"],
|
752 |
+
# # "dataset_tags": ["mozilla-foundation/common_voice_11_0", "openslr"],
|
753 |
+
# # "dataset": ["common-voice-11", "google-fleurs", "openslr53"], # a 'pretty' name for the training dataset
|
754 |
+
# "dataset": ["common-voice-11", "google-fleurs"], # a 'pretty' name for the training dataset
|
755 |
+
# # "dataset": "common-voice-11+openslr53", # a 'pretty' name for the training dataset
|
756 |
+
# "language": "bn",
|
757 |
+
# "model_name": "Whisper Small - Mohammed Rakib", # a 'pretty' name for your model
|
758 |
+
# "finetuned_from": "Rakib/whisper-small-bn-all-600",
|
759 |
+
# "tasks": "automatic-speech-recognition",
|
760 |
+
# "tags": "whisper-event",
|
761 |
+
# }
|
762 |
+
|
763 |
+
# trainer.push_to_hub(**kwargs)
|
764 |
+
trainer.push_to_hub()
|
765 |
+
|
766 |
+
|
767 |
+
print("\n\n DONEEEEEE \n\n")
|
normalizer.json
ADDED
@@ -0,0 +1,1742 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
1 |
+
{
|
2 |
+
"accessorise": "accessorize",
|
3 |
+
"accessorised": "accessorized",
|
4 |
+
"accessorises": "accessorizes",
|
5 |
+
"accessorising": "accessorizing",
|
6 |
+
"acclimatisation": "acclimatization",
|
7 |
+
"acclimatise": "acclimatize",
|
8 |
+
"acclimatised": "acclimatized",
|
9 |
+
"acclimatises": "acclimatizes",
|
10 |
+
"acclimatising": "acclimatizing",
|
11 |
+
"accoutrements": "accouterments",
|
12 |
+
"aeon": "eon",
|
13 |
+
"aeons": "eons",
|
14 |
+
"aerogramme": "aerogram",
|
15 |
+
"aerogrammes": "aerograms",
|
16 |
+
"aeroplane": "airplane",
|
17 |
+
"aeroplanes": "airplanes",
|
18 |
+
"aesthete": "esthete",
|
19 |
+
"aesthetes": "esthetes",
|
20 |
+
"aesthetic": "esthetic",
|
21 |
+
"aesthetically": "esthetically",
|
22 |
+
"aesthetics": "esthetics",
|
23 |
+
"aetiology": "etiology",
|
24 |
+
"ageing": "aging",
|
25 |
+
"aggrandisement": "aggrandizement",
|
26 |
+
"agonise": "agonize",
|
27 |
+
"agonised": "agonized",
|
28 |
+
"agonises": "agonizes",
|
29 |
+
"agonising": "agonizing",
|
30 |
+
"agonisingly": "agonizingly",
|
31 |
+
"almanack": "almanac",
|
32 |
+
"almanacks": "almanacs",
|
33 |
+
"aluminium": "aluminum",
|
34 |
+
"amortisable": "amortizable",
|
35 |
+
"amortisation": "amortization",
|
36 |
+
"amortisations": "amortizations",
|
37 |
+
"amortise": "amortize",
|
38 |
+
"amortised": "amortized",
|
39 |
+
"amortises": "amortizes",
|
40 |
+
"amortising": "amortizing",
|
41 |
+
"amphitheatre": "amphitheater",
|
42 |
+
"amphitheatres": "amphitheaters",
|
43 |
+
"anaemia": "anemia",
|
44 |
+
"anaemic": "anemic",
|
45 |
+
"anaesthesia": "anesthesia",
|
46 |
+
"anaesthetic": "anesthetic",
|
47 |
+
"anaesthetics": "anesthetics",
|
48 |
+
"anaesthetise": "anesthetize",
|
49 |
+
"anaesthetised": "anesthetized",
|
50 |
+
"anaesthetises": "anesthetizes",
|
51 |
+
"anaesthetising": "anesthetizing",
|
52 |
+
"anaesthetist": "anesthetist",
|
53 |
+
"anaesthetists": "anesthetists",
|
54 |
+
"anaesthetize": "anesthetize",
|
55 |
+
"anaesthetized": "anesthetized",
|
56 |
+
"anaesthetizes": "anesthetizes",
|
57 |
+
"anaesthetizing": "anesthetizing",
|
58 |
+
"analogue": "analog",
|
59 |
+
"analogues": "analogs",
|
60 |
+
"analyse": "analyze",
|
61 |
+
"analysed": "analyzed",
|
62 |
+
"analyses": "analyzes",
|
63 |
+
"analysing": "analyzing",
|
64 |
+
"anglicise": "anglicize",
|
65 |
+
"anglicised": "anglicized",
|
66 |
+
"anglicises": "anglicizes",
|
67 |
+
"anglicising": "anglicizing",
|
68 |
+
"annualised": "annualized",
|
69 |
+
"antagonise": "antagonize",
|
70 |
+
"antagonised": "antagonized",
|
71 |
+
"antagonises": "antagonizes",
|
72 |
+
"antagonising": "antagonizing",
|
73 |
+
"apologise": "apologize",
|
74 |
+
"apologised": "apologized",
|
75 |
+
"apologises": "apologizes",
|
76 |
+
"apologising": "apologizing",
|
77 |
+
"appal": "appall",
|
78 |
+
"appals": "appalls",
|
79 |
+
"appetiser": "appetizer",
|
80 |
+
"appetisers": "appetizers",
|
81 |
+
"appetising": "appetizing",
|
82 |
+
"appetisingly": "appetizingly",
|
83 |
+
"arbour": "arbor",
|
84 |
+
"arbours": "arbors",
|
85 |
+
"archaeologically": "archeologically",
|
86 |
+
"archaeologist": "archeologist",
|
87 |
+
"archaeologists": "archeologists",
|
88 |
+
"archaeology": "archeology</span>",
|
89 |
+
"archeological": "archaeological",
|
90 |
+
"ardour": "ardor",
|
91 |
+
"armour": "armor",
|
92 |
+
"armoured": "armored",
|
93 |
+
"armourer": "armorer",
|
94 |
+
"armourers": "armorers",
|
95 |
+
"armouries": "armories",
|
96 |
+
"armoury": "armory",
|
97 |
+
"artefact": "artifact",
|
98 |
+
"artefacts": "artifacts",
|
99 |
+
"authorise": "authorize",
|
100 |
+
"authorised": "authorized",
|
101 |
+
"authorises": "authorizes",
|
102 |
+
"authorising": "authorizing",
|
103 |
+
"axe": "ax",
|
104 |
+
"backpedalled": "backpedaled",
|
105 |
+
"backpedalling": "backpedaling",
|
106 |
+
"bannister": "banister",
|
107 |
+
"bannisters": "banisters",
|
108 |
+
"baptise": "baptize",
|
109 |
+
"baptised": "baptized",
|
110 |
+
"baptises": "baptizes",
|
111 |
+
"baptising": "baptizing",
|
112 |
+
"bastardise": "bastardize",
|
113 |
+
"bastardised": "bastardized",
|
114 |
+
"bastardises": "bastardizes",
|
115 |
+
"bastardising": "bastardizing",
|
116 |
+
"battleax": "battleaxe",
|
117 |
+
"baulk": "balk",
|
118 |
+
"baulked": "balked",
|
119 |
+
"baulking": "balking",
|
120 |
+
"baulks": "balks",
|
121 |
+
"bedevilled": "bedeviled",
|
122 |
+
"bedevilling": "bedeviling",
|
123 |
+
"behaviour": "behavior",
|
124 |
+
"behavioural": "behavioral",
|
125 |
+
"behaviourism": "behaviorism",
|
126 |
+
"behaviourist": "behaviorist",
|
127 |
+
"behaviourists": "behaviorists",
|
128 |
+
"behaviours": "behaviors",
|
129 |
+
"behove": "behoove",
|
130 |
+
"behoved": "behooved",
|
131 |
+
"behoves": "behooves",
|
132 |
+
"bejewelled": "bejeweled",
|
133 |
+
"belabour": "belabor",
|
134 |
+
"belaboured": "belabored",
|
135 |
+
"belabouring": "belaboring",
|
136 |
+
"belabours": "belabors",
|
137 |
+
"bevelled": "beveled",
|
138 |
+
"bevvies": "bevies",
|
139 |
+
"bevvy": "bevy",
|
140 |
+
"biassed": "biased",
|
141 |
+
"biassing": "biasing",
|
142 |
+
"bingeing": "binging",
|
143 |
+
"bougainvillaea": "bougainvillea",
|
144 |
+
"bougainvillaeas": "bougainvilleas",
|
145 |
+
"bowdlerise": "bowdlerize",
|
146 |
+
"bowdlerised": "bowdlerized",
|
147 |
+
"bowdlerises": "bowdlerizes",
|
148 |
+
"bowdlerising": "bowdlerizing",
|
149 |
+
"breathalyse": "breathalyze",
|
150 |
+
"breathalysed": "breathalyzed",
|
151 |
+
"breathalyser": "breathalyzer",
|
152 |
+
"breathalysers": "breathalyzers",
|
153 |
+
"breathalyses": "breathalyzes",
|
154 |
+
"breathalysing": "breathalyzing",
|
155 |
+
"brutalise": "brutalize",
|
156 |
+
"brutalised": "brutalized",
|
157 |
+
"brutalises": "brutalizes",
|
158 |
+
"brutalising": "brutalizing",
|
159 |
+
"busses": "buses",
|
160 |
+
"bussing": "busing",
|
161 |
+
"caesarean": "cesarean",
|
162 |
+
"caesareans": "cesareans",
|
163 |
+
"calibre": "caliber",
|
164 |
+
"calibres": "calibers",
|
165 |
+
"calliper": "caliper",
|
166 |
+
"callipers": "calipers",
|
167 |
+
"callisthenics": "calisthenics",
|
168 |
+
"canalise": "canalize",
|
169 |
+
"canalised": "canalized",
|
170 |
+
"canalises": "canalizes",
|
171 |
+
"canalising": "canalizing",
|
172 |
+
"cancelation": "cancellation",
|
173 |
+
"cancelations": "cancellations",
|
174 |
+
"cancelled": "canceled",
|
175 |
+
"cancelling": "canceling",
|
176 |
+
"candour": "candor",
|
177 |
+
"cannibalise": "cannibalize",
|
178 |
+
"cannibalised": "cannibalized",
|
179 |
+
"cannibalises": "cannibalizes",
|
180 |
+
"cannibalising": "cannibalizing",
|
181 |
+
"canonise": "canonize",
|
182 |
+
"canonised": "canonized",
|
183 |
+
"canonises": "canonizes",
|
184 |
+
"canonising": "canonizing",
|
185 |
+
"capitalise": "capitalize",
|
186 |
+
"capitalised": "capitalized",
|
187 |
+
"capitalises": "capitalizes",
|
188 |
+
"capitalising": "capitalizing",
|
189 |
+
"caramelise": "caramelize",
|
190 |
+
"caramelised": "caramelized",
|
191 |
+
"caramelises": "caramelizes",
|
192 |
+
"caramelising": "caramelizing",
|
193 |
+
"carbonise": "carbonize",
|
194 |
+
"carbonised": "carbonized",
|
195 |
+
"carbonises": "carbonizes",
|
196 |
+
"carbonising": "carbonizing",
|
197 |
+
"carolled": "caroled",
|
198 |
+
"carolling": "caroling",
|
199 |
+
"catalogue": "catalog",
|
200 |
+
"catalogued": "cataloged",
|
201 |
+
"catalogues": "catalogs",
|
202 |
+
"cataloguing": "cataloging",
|
203 |
+
"catalyse": "catalyze",
|
204 |
+
"catalysed": "catalyzed",
|
205 |
+
"catalyses": "catalyzes",
|
206 |
+
"catalysing": "catalyzing",
|
207 |
+
"categorise": "categorize",
|
208 |
+
"categorised": "categorized",
|
209 |
+
"categorises": "categorizes",
|
210 |
+
"categorising": "categorizing",
|
211 |
+
"cauterise": "cauterize",
|
212 |
+
"cauterised": "cauterized",
|
213 |
+
"cauterises": "cauterizes",
|
214 |
+
"cauterising": "cauterizing",
|
215 |
+
"cavilled": "caviled",
|
216 |
+
"cavilling": "caviling",
|
217 |
+
"centigramme": "centigram",
|
218 |
+
"centigrammes": "centigrams",
|
219 |
+
"centilitre": "centiliter",
|
220 |
+
"centilitres": "centiliters",
|
221 |
+
"centimetre": "centimeter",
|
222 |
+
"centimetres": "centimeters",
|
223 |
+
"centralise": "centralize",
|
224 |
+
"centralised": "centralized",
|
225 |
+
"centralises": "centralizes",
|
226 |
+
"centralising": "centralizing",
|
227 |
+
"centre": "center",
|
228 |
+
"centred": "centered",
|
229 |
+
"centrefold": "centerfold",
|
230 |
+
"centrefolds": "centerfolds",
|
231 |
+
"centrepiece": "centerpiece",
|
232 |
+
"centrepieces": "centerpieces",
|
233 |
+
"centres": "centers",
|
234 |
+
"channelled": "channeled",
|
235 |
+
"channelling": "channeling",
|
236 |
+
"characterise": "characterize",
|
237 |
+
"characterised": "characterized",
|
238 |
+
"characterises": "characterizes",
|
239 |
+
"characterising": "characterizing",
|
240 |
+
"cheque": "check",
|
241 |
+
"chequebook": "checkbook",
|
242 |
+
"chequebooks": "checkbooks",
|
243 |
+
"chequered": "checkered",
|
244 |
+
"cheques": "checks",
|
245 |
+
"chilli": "chili",
|
246 |
+
"chimaera": "chimera",
|
247 |
+
"chimaeras": "chimeras",
|
248 |
+
"chiselled": "chiseled",
|
249 |
+
"chiselling": "chiseling",
|
250 |
+
"circularise": "circularize",
|
251 |
+
"circularised": "circularized",
|
252 |
+
"circularises": "circularizes",
|
253 |
+
"circularising": "circularizing",
|
254 |
+
"civilise": "civilize",
|
255 |
+
"civilised": "civilized",
|
256 |
+
"civilises": "civilizes",
|
257 |
+
"civilising": "civilizing",
|
258 |
+
"clamour": "clamor",
|
259 |
+
"clamoured": "clamored",
|
260 |
+
"clamouring": "clamoring",
|
261 |
+
"clamours": "clamors",
|
262 |
+
"clangour": "clangor",
|
263 |
+
"clarinettist": "clarinetist",
|
264 |
+
"clarinettists": "clarinetists",
|
265 |
+
"collectivise": "collectivize",
|
266 |
+
"collectivised": "collectivized",
|
267 |
+
"collectivises": "collectivizes",
|
268 |
+
"collectivising": "collectivizing",
|
269 |
+
"colonisation": "colonization",
|
270 |
+
"colonise": "colonize",
|
271 |
+
"colonised": "colonized",
|
272 |
+
"coloniser": "colonizer",
|
273 |
+
"colonisers": "colonizers",
|
274 |
+
"colonises": "colonizes",
|
275 |
+
"colonising": "colonizing",
|
276 |
+
"colour": "color",
|
277 |
+
"colourant": "colorant",
|
278 |
+
"colourants": "colorants",
|
279 |
+
"coloured": "colored",
|
280 |
+
"coloureds": "coloreds",
|
281 |
+
"colourful": "colorful",
|
282 |
+
"colourfully": "colorfully",
|
283 |
+
"colouring": "coloring",
|
284 |
+
"colourize": "colorize",
|
285 |
+
"colourized": "colorized",
|
286 |
+
"colourizes": "colorizes",
|
287 |
+
"colourizing": "colorizing",
|
288 |
+
"colourless": "colorless",
|
289 |
+
"colours": "colors",
|
290 |
+
"commercialise": "commercialize",
|
291 |
+
"commercialised": "commercialized",
|
292 |
+
"commercialises": "commercializes",
|
293 |
+
"commercialising": "commercializing",
|
294 |
+
"compartmentalise": "compartmentalize",
|
295 |
+
"compartmentalised": "compartmentalized",
|
296 |
+
"compartmentalises": "compartmentalizes",
|
297 |
+
"compartmentalising": "compartmentalizing",
|
298 |
+
"computerise": "computerize",
|
299 |
+
"computerised": "computerized",
|
300 |
+
"computerises": "computerizes",
|
301 |
+
"computerising": "computerizing",
|
302 |
+
"conceptualise": "conceptualize",
|
303 |
+
"conceptualised": "conceptualized",
|
304 |
+
"conceptualises": "conceptualizes",
|
305 |
+
"conceptualising": "conceptualizing",
|
306 |
+
"connexion": "connection",
|
307 |
+
"connexions": "connections",
|
308 |
+
"contextualise": "contextualize",
|
309 |
+
"contextualised": "contextualized",
|
310 |
+
"contextualises": "contextualizes",
|
311 |
+
"contextualising": "contextualizing",
|
312 |
+
"cosier": "cozier",
|
313 |
+
"cosies": "cozies",
|
314 |
+
"cosiest": "coziest",
|
315 |
+
"cosily": "cozily",
|
316 |
+
"cosiness": "coziness",
|
317 |
+
"cosy": "cozy",
|
318 |
+
"councillor": "councilor",
|
319 |
+
"councillors": "councilors",
|
320 |
+
"counselled": "counseled",
|
321 |
+
"counselling": "counseling",
|
322 |
+
"counsellor": "counselor",
|
323 |
+
"counsellors": "counselors",
|
324 |
+
"crenelated": "crenellated",
|
325 |
+
"criminalise": "criminalize",
|
326 |
+
"criminalised": "criminalized",
|
327 |
+
"criminalises": "criminalizes",
|
328 |
+
"criminalising": "criminalizing",
|
329 |
+
"criticise": "criticize",
|
330 |
+
"criticised": "criticized",
|
331 |
+
"criticises": "criticizes",
|
332 |
+
"criticising": "criticizing",
|
333 |
+
"crueller": "crueler",
|
334 |
+
"cruellest": "cruelest",
|
335 |
+
"crystallisation": "crystallization",
|
336 |
+
"crystallise": "crystallize",
|
337 |
+
"crystallised": "crystallized",
|
338 |
+
"crystallises": "crystallizes",
|
339 |
+
"crystallising": "crystallizing",
|
340 |
+
"cudgelled": "cudgeled",
|
341 |
+
"cudgelling": "cudgeling",
|
342 |
+
"customise": "customize",
|
343 |
+
"customised": "customized",
|
344 |
+
"customises": "customizes",
|
345 |
+
"customising": "customizing",
|
346 |
+
"cypher": "cipher",
|
347 |
+
"cyphers": "ciphers",
|
348 |
+
"decentralisation": "decentralization",
|
349 |
+
"decentralise": "decentralize",
|
350 |
+
"decentralised": "decentralized",
|
351 |
+
"decentralises": "decentralizes",
|
352 |
+
"decentralising": "decentralizing",
|
353 |
+
"decriminalisation": "decriminalization",
|
354 |
+
"decriminalise": "decriminalize",
|
355 |
+
"decriminalised": "decriminalized",
|
356 |
+
"decriminalises": "decriminalizes",
|
357 |
+
"decriminalising": "decriminalizing",
|
358 |
+
"defence": "defense",
|
359 |
+
"defenceless": "defenseless",
|
360 |
+
"defences": "defenses",
|
361 |
+
"dehumanisation": "dehumanization",
|
362 |
+
"dehumanise": "dehumanize",
|
363 |
+
"dehumanised": "dehumanized",
|
364 |
+
"dehumanises": "dehumanizes",
|
365 |
+
"dehumanising": "dehumanizing",
|
366 |
+
"demeanour": "demeanor",
|
367 |
+
"demilitarisation": "demilitarization",
|
368 |
+
"demilitarise": "demilitarize",
|
369 |
+
"demilitarised": "demilitarized",
|
370 |
+
"demilitarises": "demilitarizes",
|
371 |
+
"demilitarising": "demilitarizing",
|
372 |
+
"demobilisation": "demobilization",
|
373 |
+
"demobilise": "demobilize",
|
374 |
+
"demobilised": "demobilized",
|
375 |
+
"demobilises": "demobilizes",
|
376 |
+
"demobilising": "demobilizing",
|
377 |
+
"democratisation": "democratization",
|
378 |
+
"democratise": "democratize",
|
379 |
+
"democratised": "democratized",
|
380 |
+
"democratises": "democratizes",
|
381 |
+
"democratising": "democratizing",
|
382 |
+
"demonise": "demonize",
|
383 |
+
"demonised": "demonized",
|
384 |
+
"demonises": "demonizes",
|
385 |
+
"demonising": "demonizing",
|
386 |
+
"demoralisation": "demoralization",
|
387 |
+
"demoralise": "demoralize",
|
388 |
+
"demoralised": "demoralized",
|
389 |
+
"demoralises": "demoralizes",
|
390 |
+
"demoralising": "demoralizing",
|
391 |
+
"denationalisation": "denationalization",
|
392 |
+
"denationalise": "denationalize",
|
393 |
+
"denationalised": "denationalized",
|
394 |
+
"denationalises": "denationalizes",
|
395 |
+
"denationalising": "denationalizing",
|
396 |
+
"deodorise": "deodorize",
|
397 |
+
"deodorised": "deodorized",
|
398 |
+
"deodorises": "deodorizes",
|
399 |
+
"deodorising": "deodorizing",
|
400 |
+
"depersonalise": "depersonalize",
|
401 |
+
"depersonalised": "depersonalized",
|
402 |
+
"depersonalises": "depersonalizes",
|
403 |
+
"depersonalising": "depersonalizing",
|
404 |
+
"deputise": "deputize",
|
405 |
+
"deputised": "deputized",
|
406 |
+
"deputises": "deputizes",
|
407 |
+
"deputising": "deputizing",
|
408 |
+
"desensitisation": "desensitization",
|
409 |
+
"desensitise": "desensitize",
|
410 |
+
"desensitised": "desensitized",
|
411 |
+
"desensitises": "desensitizes",
|
412 |
+
"desensitising": "desensitizing",
|
413 |
+
"destabilisation": "destabilization",
|
414 |
+
"destabilise": "destabilize",
|
415 |
+
"destabilised": "destabilized",
|
416 |
+
"destabilises": "destabilizes",
|
417 |
+
"destabilising": "destabilizing",
|
418 |
+
"dialled": "dialed",
|
419 |
+
"dialling": "dialing",
|
420 |
+
"dialogue": "dialog",
|
421 |
+
"dialogues": "dialogs",
|
422 |
+
"diarrhoea": "diarrhea",
|
423 |
+
"digitise": "digitize",
|
424 |
+
"digitised": "digitized",
|
425 |
+
"digitises": "digitizes",
|
426 |
+
"digitising": "digitizing",
|
427 |
+
"disc": "disk",
|
428 |
+
"discolour": "discolor",
|
429 |
+
"discoloured": "discolored",
|
430 |
+
"discolouring": "discoloring",
|
431 |
+
"discolours": "discolors",
|
432 |
+
"discs": "disks",
|
433 |
+
"disembowelled": "disemboweled",
|
434 |
+
"disembowelling": "disemboweling",
|
435 |
+
"disfavour": "disfavor",
|
436 |
+
"dishevelled": "disheveled",
|
437 |
+
"dishonour": "dishonor",
|
438 |
+
"dishonourable": "dishonorable",
|
439 |
+
"dishonourably": "dishonorably",
|
440 |
+
"dishonoured": "dishonored",
|
441 |
+
"dishonouring": "dishonoring",
|
442 |
+
"dishonours": "dishonors",
|
443 |
+
"disorganisation": "disorganization",
|
444 |
+
"disorganised": "disorganized",
|
445 |
+
"distil": "distill",
|
446 |
+
"distils": "distills",
|
447 |
+
"dramatisation": "dramatization",
|
448 |
+
"dramatisations": "dramatizations",
|
449 |
+
"dramatise": "dramatize",
|
450 |
+
"dramatised": "dramatized",
|
451 |
+
"dramatises": "dramatizes",
|
452 |
+
"dramatising": "dramatizing",
|
453 |
+
"draught": "draft",
|
454 |
+
"draughtboard": "draftboard",
|
455 |
+
"draughtboards": "draftboards",
|
456 |
+
"draughtier": "draftier",
|
457 |
+
"draughtiest": "draftiest",
|
458 |
+
"draughts": "drafts",
|
459 |
+
"draughtsman": "draftsman",
|
460 |
+
"draughtsmanship": "draftsmanship",
|
461 |
+
"draughtsmen": "draftsmen",
|
462 |
+
"draughtswoman": "draftswoman",
|
463 |
+
"draughtswomen": "draftswomen",
|
464 |
+
"draughty": "drafty",
|
465 |
+
"drivelled": "driveled",
|
466 |
+
"drivelling": "driveling",
|
467 |
+
"duelled": "dueled",
|
468 |
+
"duelling": "dueling",
|
469 |
+
"economise": "economize",
|
470 |
+
"economised": "economized",
|
471 |
+
"economises": "economizes",
|
472 |
+
"economising": "economizing",
|
473 |
+
"editorialise": "editorialize",
|
474 |
+
"editorialised": "editorialized",
|
475 |
+
"editorialises": "editorializes",
|
476 |
+
"editorialising": "editorializing",
|
477 |
+
"edoema": "edema",
|
478 |
+
"empathise": "empathize",
|
479 |
+
"empathised": "empathized",
|
480 |
+
"empathises": "empathizes",
|
481 |
+
"empathising": "empathizing",
|
482 |
+
"emphasise": "emphasize",
|
483 |
+
"emphasised": "emphasized",
|
484 |
+
"emphasises": "emphasizes",
|
485 |
+
"emphasising": "emphasizing",
|
486 |
+
"enamelled": "enameled",
|
487 |
+
"enamelling": "enameling",
|
488 |
+
"enamoured": "enamored",
|
489 |
+
"encyclopaedia": "encyclopedia",
|
490 |
+
"encyclopaedias": "encyclopedias",
|
491 |
+
"encyclopaedic": "encyclopedic",
|
492 |
+
"endeavour": "endeavor",
|
493 |
+
"endeavoured": "endeavored",
|
494 |
+
"endeavouring": "endeavoring",
|
495 |
+
"endeavours": "endeavors",
|
496 |
+
"energise": "energize",
|
497 |
+
"energised": "energized",
|
498 |
+
"energises": "energizes",
|
499 |
+
"energising": "energizing",
|
500 |
+
"enrol": "enroll",
|
501 |
+
"enrols": "enrolls",
|
502 |
+
"enthral": "enthrall",
|
503 |
+
"enthrals": "enthralls",
|
504 |
+
"epaulette": "epaulet",
|
505 |
+
"epaulettes": "epaulets",
|
506 |
+
"epicentre": "epicenter",
|
507 |
+
"epicentres": "epicenters",
|
508 |
+
"epilogue": "epilog",
|
509 |
+
"epilogues": "epilogs",
|
510 |
+
"epitomise": "epitomize",
|
511 |
+
"epitomised": "epitomized",
|
512 |
+
"epitomises": "epitomizes",
|
513 |
+
"epitomising": "epitomizing",
|
514 |
+
"equalisation": "equalization",
|
515 |
+
"equalise": "equalize",
|
516 |
+
"equalised": "equalized",
|
517 |
+
"equaliser": "equalizer",
|
518 |
+
"equalisers": "equalizers",
|
519 |
+
"equalises": "equalizes",
|
520 |
+
"equalising": "equalizing",
|
521 |
+
"eulogise": "eulogize",
|
522 |
+
"eulogised": "eulogized",
|
523 |
+
"eulogises": "eulogizes",
|
524 |
+
"eulogising": "eulogizing",
|
525 |
+
"evangelise": "evangelize",
|
526 |
+
"evangelised": "evangelized",
|
527 |
+
"evangelises": "evangelizes",
|
528 |
+
"evangelising": "evangelizing",
|
529 |
+
"exorcise": "exorcize",
|
530 |
+
"exorcised": "exorcized",
|
531 |
+
"exorcises": "exorcizes",
|
532 |
+
"exorcising": "exorcizing",
|
533 |
+
"extemporisation": "extemporization",
|
534 |
+
"extemporise": "extemporize",
|
535 |
+
"extemporised": "extemporized",
|
536 |
+
"extemporises": "extemporizes",
|
537 |
+
"extemporising": "extemporizing",
|
538 |
+
"externalisation": "externalization",
|
539 |
+
"externalisations": "externalizations",
|
540 |
+
"externalise": "externalize",
|
541 |
+
"externalised": "externalized",
|
542 |
+
"externalises": "externalizes",
|
543 |
+
"externalising": "externalizing",
|
544 |
+
"factorise": "factorize",
|
545 |
+
"factorised": "factorized",
|
546 |
+
"factorises": "factorizes",
|
547 |
+
"factorising": "factorizing",
|
548 |
+
"faecal": "fecal",
|
549 |
+
"faeces": "feces",
|
550 |
+
"familiarisation": "familiarization",
|
551 |
+
"familiarise": "familiarize",
|
552 |
+
"familiarised": "familiarized",
|
553 |
+
"familiarises": "familiarizes",
|
554 |
+
"familiarising": "familiarizing",
|
555 |
+
"fantasise": "fantasize",
|
556 |
+
"fantasised": "fantasized",
|
557 |
+
"fantasises": "fantasizes",
|
558 |
+
"fantasising": "fantasizing",
|
559 |
+
"favour": "favor",
|
560 |
+
"favourable": "favorable",
|
561 |
+
"favourably": "favorably",
|
562 |
+
"favoured": "favored",
|
563 |
+
"favouring": "favoring",
|
564 |
+
"favourite": "favorite",
|
565 |
+
"favourites": "favorites",
|
566 |
+
"favouritism": "favoritism",
|
567 |
+
"favours": "favors",
|
568 |
+
"feminise": "feminize",
|
569 |
+
"feminised": "feminized",
|
570 |
+
"feminises": "feminizes",
|
571 |
+
"feminising": "feminizing",
|
572 |
+
"fertilisation": "fertilization",
|
573 |
+
"fertilise": "fertilize",
|
574 |
+
"fertilised": "fertilized",
|
575 |
+
"fertiliser": "fertilizer",
|
576 |
+
"fertilisers": "fertilizers",
|
577 |
+
"fertilises": "fertilizes",
|
578 |
+
"fertilising": "fertilizing",
|
579 |
+
"fervour": "fervor",
|
580 |
+
"fibre": "fiber",
|
581 |
+
"fibreglass": "fiberglass",
|
582 |
+
"fibres": "fibers",
|
583 |
+
"fictionalisation": "fictionalization",
|
584 |
+
"fictionalisations": "fictionalizations",
|
585 |
+
"fictionalise": "fictionalize",
|
586 |
+
"fictionalised": "fictionalized",
|
587 |
+
"fictionalises": "fictionalizes",
|
588 |
+
"fictionalising": "fictionalizing",
|
589 |
+
"fillet": "filet",
|
590 |
+
"filleted": "fileted",
|
591 |
+
"filleting": "fileting",
|
592 |
+
"fillets": "filets",
|
593 |
+
"finalisation": "finalization",
|
594 |
+
"finalise": "finalize",
|
595 |
+
"finalised": "finalized",
|
596 |
+
"finalises": "finalizes",
|
597 |
+
"finalising": "finalizing",
|
598 |
+
"flautist": "flutist",
|
599 |
+
"flautists": "flutists",
|
600 |
+
"flavour": "flavor",
|
601 |
+
"flavoured": "flavored",
|
602 |
+
"flavouring": "flavoring",
|
603 |
+
"flavourings": "flavorings",
|
604 |
+
"flavourless": "flavorless",
|
605 |
+
"flavours": "flavors",
|
606 |
+
"flavoursome": "flavorsome",
|
607 |
+
"flyer / flier": "flier / flyer",
|
608 |
+
"foetal": "fetal",
|
609 |
+
"foetid": "fetid",
|
610 |
+
"foetus": "fetus",
|
611 |
+
"foetuses": "fetuses",
|
612 |
+
"formalisation": "formalization",
|
613 |
+
"formalise": "formalize",
|
614 |
+
"formalised": "formalized",
|
615 |
+
"formalises": "formalizes",
|
616 |
+
"formalising": "formalizing",
|
617 |
+
"fossilisation": "fossilization",
|
618 |
+
"fossilise": "fossilize",
|
619 |
+
"fossilised": "fossilized",
|
620 |
+
"fossilises": "fossilizes",
|
621 |
+
"fossilising": "fossilizing",
|
622 |
+
"fraternisation": "fraternization",
|
623 |
+
"fraternise": "fraternize",
|
624 |
+
"fraternised": "fraternized",
|
625 |
+
"fraternises": "fraternizes",
|
626 |
+
"fraternising": "fraternizing",
|
627 |
+
"fulfil": "fulfill",
|
628 |
+
"fulfilment": "fulfillment",
|
629 |
+
"fulfils": "fulfills",
|
630 |
+
"funnelled": "funneled",
|
631 |
+
"funnelling": "funneling",
|
632 |
+
"gage": "gauge",
|
633 |
+
"gaged": "gauged",
|
634 |
+
"gages": "gauges",
|
635 |
+
"gaging": "gauging",
|
636 |
+
"galvanise": "galvanize",
|
637 |
+
"galvanised": "galvanized",
|
638 |
+
"galvanises": "galvanizes",
|
639 |
+
"galvanising": "galvanizing",
|
640 |
+
"gambolled": "gamboled",
|
641 |
+
"gambolling": "gamboling",
|
642 |
+
"gaol": "jail",
|
643 |
+
"gaolbird": "jailbird",
|
644 |
+
"gaolbirds": "jailbirds",
|
645 |
+
"gaolbreak": "jailbreak",
|
646 |
+
"gaolbreaks": "jailbreaks",
|
647 |
+
"gaoled": "jailed",
|
648 |
+
"gaoler": "jailer",
|
649 |
+
"gaolers": "jailers",
|
650 |
+
"gaoling": "jailing",
|
651 |
+
"gaols": "jails",
|
652 |
+
"gasses": "gases",
|
653 |
+
"generalisation": "generalization",
|
654 |
+
"generalisations": "generalizations",
|
655 |
+
"generalise": "generalize",
|
656 |
+
"generalised": "generalized",
|
657 |
+
"generalises": "generalizes",
|
658 |
+
"generalising": "generalizing",
|
659 |
+
"ghettoise": "ghettoize",
|
660 |
+
"ghettoised": "ghettoized",
|
661 |
+
"ghettoises": "ghettoizes",
|
662 |
+
"ghettoising": "ghettoizing",
|
663 |
+
"gipsies": "gypsies",
|
664 |
+
"glamor": "glamour",
|
665 |
+
"glamorise": "glamorize",
|
666 |
+
"glamorised": "glamorized",
|
667 |
+
"glamorises": "glamorizes",
|
668 |
+
"glamorising": "glamorizing",
|
669 |
+
"globalisation": "globalization",
|
670 |
+
"globalise": "globalize",
|
671 |
+
"globalised": "globalized",
|
672 |
+
"globalises": "globalizes",
|
673 |
+
"globalising": "globalizing",
|
674 |
+
"glueing": "gluing",
|
675 |
+
"goitre": "goiter",
|
676 |
+
"goitres": "goiters",
|
677 |
+
"gonorrhoea": "gonorrhea",
|
678 |
+
"gramme": "gram",
|
679 |
+
"grammes": "grams",
|
680 |
+
"gravelled": "graveled",
|
681 |
+
"grey": "gray",
|
682 |
+
"greyed": "grayed",
|
683 |
+
"greying": "graying",
|
684 |
+
"greyish": "grayish",
|
685 |
+
"greyness": "grayness",
|
686 |
+
"greys": "grays",
|
687 |
+
"grovelled": "groveled",
|
688 |
+
"grovelling": "groveling",
|
689 |
+
"groyne": "groin",
|
690 |
+
"groynes": "groins",
|
691 |
+
"gruelling": "grueling",
|
692 |
+
"gruellingly": "gruelingly",
|
693 |
+
"gryphon": "griffin",
|
694 |
+
"gryphons": "griffins",
|
695 |
+
"gynaecological": "gynecological",
|
696 |
+
"gynaecologist": "gynecologist",
|
697 |
+
"gynaecologists": "gynecologists",
|
698 |
+
"gynaecology": "gynecology",
|
699 |
+
"haematological": "hematological",
|
700 |
+
"haematologist": "hematologist",
|
701 |
+
"haematologists": "hematologists",
|
702 |
+
"haematology": "hematology",
|
703 |
+
"haemoglobin": "hemoglobin",
|
704 |
+
"haemophilia": "hemophilia",
|
705 |
+
"haemophiliac": "hemophiliac",
|
706 |
+
"haemophiliacs": "hemophiliacs",
|
707 |
+
"haemorrhage": "hemorrhage",
|
708 |
+
"haemorrhaged": "hemorrhaged",
|
709 |
+
"haemorrhages": "hemorrhages",
|
710 |
+
"haemorrhaging": "hemorrhaging",
|
711 |
+
"haemorrhoids": "hemorrhoids",
|
712 |
+
"harbour": "harbor",
|
713 |
+
"harboured": "harbored",
|
714 |
+
"harbouring": "harboring",
|
715 |
+
"harbours": "harbors",
|
716 |
+
"harmonisation": "harmonization",
|
717 |
+
"harmonise": "harmonize",
|
718 |
+
"harmonised": "harmonized",
|
719 |
+
"harmonises": "harmonizes",
|
720 |
+
"harmonising": "harmonizing",
|
721 |
+
"homoeopath": "homeopath",
|
722 |
+
"homoeopathic": "homeopathic",
|
723 |
+
"homoeopaths": "homeopaths",
|
724 |
+
"homoeopathy": "homeopathy",
|
725 |
+
"homogenise": "homogenize",
|
726 |
+
"homogenised": "homogenized",
|
727 |
+
"homogenises": "homogenizes",
|
728 |
+
"homogenising": "homogenizing",
|
729 |
+
"honour": "honor",
|
730 |
+
"honourable": "honorable",
|
731 |
+
"honourably": "honorably",
|
732 |
+
"honoured": "honored",
|
733 |
+
"honouring": "honoring",
|
734 |
+
"honours": "honors",
|
735 |
+
"hospitalisation": "hospitalization",
|
736 |
+
"hospitalise": "hospitalize",
|
737 |
+
"hospitalised": "hospitalized",
|
738 |
+
"hospitalises": "hospitalizes",
|
739 |
+
"hospitalising": "hospitalizing",
|
740 |
+
"humanise": "humanize",
|
741 |
+
"humanised": "humanized",
|
742 |
+
"humanises": "humanizes",
|
743 |
+
"humanising": "humanizing",
|
744 |
+
"humour": "humor",
|
745 |
+
"humoured": "humored",
|
746 |
+
"humouring": "humoring",
|
747 |
+
"humourless": "humorless",
|
748 |
+
"humours": "humors",
|
749 |
+
"hybridise": "hybridize",
|
750 |
+
"hybridised": "hybridized",
|
751 |
+
"hybridises": "hybridizes",
|
752 |
+
"hybridising": "hybridizing",
|
753 |
+
"hypnotise": "hypnotize",
|
754 |
+
"hypnotised": "hypnotized",
|
755 |
+
"hypnotises": "hypnotizes",
|
756 |
+
"hypnotising": "hypnotizing",
|
757 |
+
"hypothesise": "hypothesize",
|
758 |
+
"hypothesised": "hypothesized",
|
759 |
+
"hypothesises": "hypothesizes",
|
760 |
+
"hypothesising": "hypothesizing",
|
761 |
+
"idealisation": "idealization",
|
762 |
+
"idealise": "idealize",
|
763 |
+
"idealised": "idealized",
|
764 |
+
"idealises": "idealizes",
|
765 |
+
"idealising": "idealizing",
|
766 |
+
"idolise": "idolize",
|
767 |
+
"idolised": "idolized",
|
768 |
+
"idolises": "idolizes",
|
769 |
+
"idolising": "idolizing",
|
770 |
+
"immobilisation": "immobilization",
|
771 |
+
"immobilise": "immobilize",
|
772 |
+
"immobilised": "immobilized",
|
773 |
+
"immobiliser": "immobilizer",
|
774 |
+
"immobilisers": "immobilizers",
|
775 |
+
"immobilises": "immobilizes",
|
776 |
+
"immobilising": "immobilizing",
|
777 |
+
"immortalise": "immortalize",
|
778 |
+
"immortalised": "immortalized",
|
779 |
+
"immortalises": "immortalizes",
|
780 |
+
"immortalising": "immortalizing",
|
781 |
+
"immunisation": "immunization",
|
782 |
+
"immunise": "immunize",
|
783 |
+
"immunised": "immunized",
|
784 |
+
"immunises": "immunizes",
|
785 |
+
"immunising": "immunizing",
|
786 |
+
"impanelled": "impaneled",
|
787 |
+
"impanelling": "impaneling",
|
788 |
+
"imperilled": "imperiled",
|
789 |
+
"imperilling": "imperiling",
|
790 |
+
"individualise": "individualize",
|
791 |
+
"individualised": "individualized",
|
792 |
+
"individualises": "individualizes",
|
793 |
+
"individualising": "individualizing",
|
794 |
+
"industrialise": "industrialize",
|
795 |
+
"industrialised": "industrialized",
|
796 |
+
"industrialises": "industrializes",
|
797 |
+
"industrialising": "industrializing",
|
798 |
+
"inflexion": "inflection",
|
799 |
+
"inflexions": "inflections",
|
800 |
+
"initialise": "initialize",
|
801 |
+
"initialised": "initialized",
|
802 |
+
"initialises": "initializes",
|
803 |
+
"initialising": "initializing",
|
804 |
+
"initialled": "initialed",
|
805 |
+
"initialling": "initialing",
|
806 |
+
"instal": "install",
|
807 |
+
"instalment": "installment",
|
808 |
+
"instalments": "installments",
|
809 |
+
"instals": "installs",
|
810 |
+
"instil": "instill",
|
811 |
+
"instils": "instills",
|
812 |
+
"institutionalisation": "institutionalization",
|
813 |
+
"institutionalise": "institutionalize",
|
814 |
+
"institutionalised": "institutionalized",
|
815 |
+
"institutionalises": "institutionalizes",
|
816 |
+
"institutionalising": "institutionalizing",
|
817 |
+
"intellectualise": "intellectualize",
|
818 |
+
"intellectualised": "intellectualized",
|
819 |
+
"intellectualises": "intellectualizes",
|
820 |
+
"intellectualising": "intellectualizing",
|
821 |
+
"internalisation": "internalization",
|
822 |
+
"internalise": "internalize",
|
823 |
+
"internalised": "internalized",
|
824 |
+
"internalises": "internalizes",
|
825 |
+
"internalising": "internalizing",
|
826 |
+
"internationalisation": "internationalization",
|
827 |
+
"internationalise": "internationalize",
|
828 |
+
"internationalised": "internationalized",
|
829 |
+
"internationalises": "internationalizes",
|
830 |
+
"internationalising": "internationalizing",
|
831 |
+
"ionisation": "ionization",
|
832 |
+
"ionise": "ionize",
|
833 |
+
"ionised": "ionized",
|
834 |
+
"ioniser": "ionizer",
|
835 |
+
"ionisers": "ionizers",
|
836 |
+
"ionises": "ionizes",
|
837 |
+
"ionising": "ionizing",
|
838 |
+
"italicise": "italicize",
|
839 |
+
"italicised": "italicized",
|
840 |
+
"italicises": "italicizes",
|
841 |
+
"italicising": "italicizing",
|
842 |
+
"itemise": "itemize",
|
843 |
+
"itemised": "itemized",
|
844 |
+
"itemises": "itemizes",
|
845 |
+
"itemising": "itemizing",
|
846 |
+
"jeopardise": "jeopardize",
|
847 |
+
"jeopardised": "jeopardized",
|
848 |
+
"jeopardises": "jeopardizes",
|
849 |
+
"jeopardising": "jeopardizing",
|
850 |
+
"jewelled": "jeweled",
|
851 |
+
"jeweller": "jeweler",
|
852 |
+
"jewellers": "jewelers",
|
853 |
+
"jewellery": "jewelry",
|
854 |
+
"judgement": "judgment",
|
855 |
+
"kilogramme": "kilogram",
|
856 |
+
"kilogrammes": "kilograms",
|
857 |
+
"kilometre": "kilometer",
|
858 |
+
"kilometres": "kilometers",
|
859 |
+
"labelled": "labeled",
|
860 |
+
"labelling": "labeling",
|
861 |
+
"labour": "labor",
|
862 |
+
"laboured": "labored",
|
863 |
+
"labourer": "laborer",
|
864 |
+
"labourers": "laborers",
|
865 |
+
"labouring": "laboring",
|
866 |
+
"labours": "labors",
|
867 |
+
"lacklustre": "lackluster",
|
868 |
+
"legalisation": "legalization",
|
869 |
+
"legalise": "legalize",
|
870 |
+
"legalised": "legalized",
|
871 |
+
"legalises": "legalizes",
|
872 |
+
"legalising": "legalizing",
|
873 |
+
"legitimise": "legitimize",
|
874 |
+
"legitimised": "legitimized",
|
875 |
+
"legitimises": "legitimizes",
|
876 |
+
"legitimising": "legitimizing",
|
877 |
+
"leukaemia": "leukemia",
|
878 |
+
"levelled": "leveled",
|
879 |
+
"leveller": "leveler",
|
880 |
+
"levellers": "levelers",
|
881 |
+
"levelling": "leveling",
|
882 |
+
"libelled": "libeled",
|
883 |
+
"libelling": "libeling",
|
884 |
+
"libellous": "libelous",
|
885 |
+
"liberalisation": "liberalization",
|
886 |
+
"liberalise": "liberalize",
|
887 |
+
"liberalised": "liberalized",
|
888 |
+
"liberalises": "liberalizes",
|
889 |
+
"liberalising": "liberalizing",
|
890 |
+
"licence": "license",
|
891 |
+
"licenced": "licensed",
|
892 |
+
"licences": "licenses",
|
893 |
+
"licencing": "licensing",
|
894 |
+
"likeable": "likable",
|
895 |
+
"lionisation": "lionization",
|
896 |
+
"lionise": "lionize",
|
897 |
+
"lionised": "lionized",
|
898 |
+
"lionises": "lionizes",
|
899 |
+
"lionising": "lionizing",
|
900 |
+
"liquidise": "liquidize",
|
901 |
+
"liquidised": "liquidized",
|
902 |
+
"liquidiser": "liquidizer",
|
903 |
+
"liquidisers": "liquidizers",
|
904 |
+
"liquidises": "liquidizes",
|
905 |
+
"liquidising": "liquidizing",
|
906 |
+
"litre": "liter",
|
907 |
+
"litres": "liters",
|
908 |
+
"localise": "localize",
|
909 |
+
"localised": "localized",
|
910 |
+
"localises": "localizes",
|
911 |
+
"localising": "localizing",
|
912 |
+
"louvre": "louver",
|
913 |
+
"louvred": "louvered",
|
914 |
+
"louvres": "louvers",
|
915 |
+
"lustre": "luster",
|
916 |
+
"magnetise": "magnetize",
|
917 |
+
"magnetised": "magnetized",
|
918 |
+
"magnetises": "magnetizes",
|
919 |
+
"magnetising": "magnetizing",
|
920 |
+
"manoeuvrability": "maneuverability",
|
921 |
+
"manoeuvrable": "maneuverable",
|
922 |
+
"manoeuvre": "maneuver",
|
923 |
+
"manoeuvred": "maneuvered",
|
924 |
+
"manoeuvres": "maneuvers",
|
925 |
+
"manoeuvring": "maneuvering",
|
926 |
+
"manoeuvrings": "maneuverings",
|
927 |
+
"marginalisation": "marginalization",
|
928 |
+
"marginalise": "marginalize",
|
929 |
+
"marginalised": "marginalized",
|
930 |
+
"marginalises": "marginalizes",
|
931 |
+
"marginalising": "marginalizing",
|
932 |
+
"marshalled": "marshaled",
|
933 |
+
"marshalling": "marshaling",
|
934 |
+
"marvelled": "marveled",
|
935 |
+
"marvelling": "marveling",
|
936 |
+
"marvellous": "marvelous",
|
937 |
+
"marvellously": "marvelously",
|
938 |
+
"materialisation": "materialization",
|
939 |
+
"materialise": "materialize",
|
940 |
+
"materialised": "materialized",
|
941 |
+
"materialises": "materializes",
|
942 |
+
"materialising": "materializing",
|
943 |
+
"maximisation": "maximization",
|
944 |
+
"maximise": "maximize",
|
945 |
+
"maximised": "maximized",
|
946 |
+
"maximises": "maximizes",
|
947 |
+
"maximising": "maximizing",
|
948 |
+
"meagre": "meager",
|
949 |
+
"mechanisation": "mechanization",
|
950 |
+
"mechanise": "mechanize",
|
951 |
+
"mechanised": "mechanized",
|
952 |
+
"mechanises": "mechanizes",
|
953 |
+
"mechanising": "mechanizing",
|
954 |
+
"mediaeval": "medieval",
|
955 |
+
"memorialise": "memorialize",
|
956 |
+
"memorialised": "memorialized",
|
957 |
+
"memorialises": "memorializes",
|
958 |
+
"memorialising": "memorializing",
|
959 |
+
"memorise": "memorize",
|
960 |
+
"memorised": "memorized",
|
961 |
+
"memorises": "memorizes",
|
962 |
+
"memorising": "memorizing",
|
963 |
+
"mesmerise": "mesmerize",
|
964 |
+
"mesmerised": "mesmerized",
|
965 |
+
"mesmerises": "mesmerizes",
|
966 |
+
"mesmerising": "mesmerizing",
|
967 |
+
"metabolise": "metabolize",
|
968 |
+
"metabolised": "metabolized",
|
969 |
+
"metabolises": "metabolizes",
|
970 |
+
"metabolising": "metabolizing",
|
971 |
+
"metre": "meter",
|
972 |
+
"metres": "meters",
|
973 |
+
"mhm": "hmm",
|
974 |
+
"micrometre": "micrometer",
|
975 |
+
"micrometres": "micrometers",
|
976 |
+
"militarise": "militarize",
|
977 |
+
"militarised": "militarized",
|
978 |
+
"militarises": "militarizes",
|
979 |
+
"militarising": "militarizing",
|
980 |
+
"milligramme": "milligram",
|
981 |
+
"milligrammes": "milligrams",
|
982 |
+
"millilitre": "milliliter",
|
983 |
+
"millilitres": "milliliters",
|
984 |
+
"millimetre": "millimeter",
|
985 |
+
"millimetres": "millimeters",
|
986 |
+
"miniaturisation": "miniaturization",
|
987 |
+
"miniaturise": "miniaturize",
|
988 |
+
"miniaturised": "miniaturized",
|
989 |
+
"miniaturises": "miniaturizes",
|
990 |
+
"miniaturising": "miniaturizing",
|
991 |
+
"minibusses": "minibuses",
|
992 |
+
"minimise": "minimize",
|
993 |
+
"minimised": "minimized",
|
994 |
+
"minimises": "minimizes",
|
995 |
+
"minimising": "minimizing",
|
996 |
+
"misbehaviour": "misbehavior",
|
997 |
+
"misdemeanour": "misdemeanor",
|
998 |
+
"misdemeanours": "misdemeanors",
|
999 |
+
"misspelt": "misspelled",
|
1000 |
+
"mitre": "miter",
|
1001 |
+
"mitres": "miters",
|
1002 |
+
"mm": "hmm",
|
1003 |
+
"mmm": "hmm",
|
1004 |
+
"mobilisation": "mobilization",
|
1005 |
+
"mobilise": "mobilize",
|
1006 |
+
"mobilised": "mobilized",
|
1007 |
+
"mobilises": "mobilizes",
|
1008 |
+
"mobilising": "mobilizing",
|
1009 |
+
"modelled": "modeled",
|
1010 |
+
"modeller": "modeler",
|
1011 |
+
"modellers": "modelers",
|
1012 |
+
"modelling": "modeling",
|
1013 |
+
"modernise": "modernize",
|
1014 |
+
"modernised": "modernized",
|
1015 |
+
"modernises": "modernizes",
|
1016 |
+
"modernising": "modernizing",
|
1017 |
+
"moisturise": "moisturize",
|
1018 |
+
"moisturised": "moisturized",
|
1019 |
+
"moisturiser": "moisturizer",
|
1020 |
+
"moisturisers": "moisturizers",
|
1021 |
+
"moisturises": "moisturizes",
|
1022 |
+
"moisturising": "moisturizing",
|
1023 |
+
"monologue": "monolog",
|
1024 |
+
"monologues": "monologs",
|
1025 |
+
"monopolisation": "monopolization",
|
1026 |
+
"monopolise": "monopolize",
|
1027 |
+
"monopolised": "monopolized",
|
1028 |
+
"monopolises": "monopolizes",
|
1029 |
+
"monopolising": "monopolizing",
|
1030 |
+
"moralise": "moralize",
|
1031 |
+
"moralised": "moralized",
|
1032 |
+
"moralises": "moralizes",
|
1033 |
+
"moralising": "moralizing",
|
1034 |
+
"motorised": "motorized",
|
1035 |
+
"mould": "mold",
|
1036 |
+
"moulded": "molded",
|
1037 |
+
"moulder": "molder",
|
1038 |
+
"mouldered": "moldered",
|
1039 |
+
"mouldering": "moldering",
|
1040 |
+
"moulders": "molders",
|
1041 |
+
"mouldier": "moldier",
|
1042 |
+
"mouldiest": "moldiest",
|
1043 |
+
"moulding": "molding",
|
1044 |
+
"mouldings": "moldings",
|
1045 |
+
"moulds": "molds",
|
1046 |
+
"mouldy": "moldy",
|
1047 |
+
"moult": "molt",
|
1048 |
+
"moulted": "molted",
|
1049 |
+
"moulting": "molting",
|
1050 |
+
"moults": "molts",
|
1051 |
+
"moustache": "mustache",
|
1052 |
+
"moustached": "mustached",
|
1053 |
+
"moustaches": "mustaches",
|
1054 |
+
"moustachioed": "mustachioed",
|
1055 |
+
"multicoloured": "multicolored",
|
1056 |
+
"nationalisation": "nationalization",
|
1057 |
+
"nationalisations": "nationalizations",
|
1058 |
+
"nationalise": "nationalize",
|
1059 |
+
"nationalised": "nationalized",
|
1060 |
+
"nationalises": "nationalizes",
|
1061 |
+
"nationalising": "nationalizing",
|
1062 |
+
"naturalisation": "naturalization",
|
1063 |
+
"naturalise": "naturalize",
|
1064 |
+
"naturalised": "naturalized",
|
1065 |
+
"naturalises": "naturalizes",
|
1066 |
+
"naturalising": "naturalizing",
|
1067 |
+
"neighbour": "neighbor",
|
1068 |
+
"neighbourhood": "neighborhood",
|
1069 |
+
"neighbourhoods": "neighborhoods",
|
1070 |
+
"neighbouring": "neighboring",
|
1071 |
+
"neighbourliness": "neighborliness",
|
1072 |
+
"neighbourly": "neighborly",
|
1073 |
+
"neighbours": "neighbors",
|
1074 |
+
"neutralisation": "neutralization",
|
1075 |
+
"neutralise": "neutralize",
|
1076 |
+
"neutralised": "neutralized",
|
1077 |
+
"neutralises": "neutralizes",
|
1078 |
+
"neutralising": "neutralizing",
|
1079 |
+
"normalisation": "normalization",
|
1080 |
+
"normalise": "normalize",
|
1081 |
+
"normalised": "normalized",
|
1082 |
+
"normalises": "normalizes",
|
1083 |
+
"normalising": "normalizing",
|
1084 |
+
"odour": "odor",
|
1085 |
+
"odourless": "odorless",
|
1086 |
+
"odours": "odors",
|
1087 |
+
"oesophagus": "esophagus",
|
1088 |
+
"oesophaguses": "esophaguses",
|
1089 |
+
"oestrogen": "estrogen",
|
1090 |
+
"offence": "offense",
|
1091 |
+
"offences": "offenses",
|
1092 |
+
"omelette": "omelet",
|
1093 |
+
"omelettes": "omelets",
|
1094 |
+
"optimise": "optimize",
|
1095 |
+
"optimised": "optimized",
|
1096 |
+
"optimises": "optimizes",
|
1097 |
+
"optimising": "optimizing",
|
1098 |
+
"organisation": "organization",
|
1099 |
+
"organisational": "organizational",
|
1100 |
+
"organisations": "organizations",
|
1101 |
+
"organise": "organize",
|
1102 |
+
"organised": "organized",
|
1103 |
+
"organiser": "organizer",
|
1104 |
+
"organisers": "organizers",
|
1105 |
+
"organises": "organizes",
|
1106 |
+
"organising": "organizing",
|
1107 |
+
"orthopaedic": "orthopedic",
|
1108 |
+
"orthopaedics": "orthopedics",
|
1109 |
+
"ostracise": "ostracize",
|
1110 |
+
"ostracised": "ostracized",
|
1111 |
+
"ostracises": "ostracizes",
|
1112 |
+
"ostracising": "ostracizing",
|
1113 |
+
"outmanoeuvre": "outmaneuver",
|
1114 |
+
"outmanoeuvred": "outmaneuvered",
|
1115 |
+
"outmanoeuvres": "outmaneuvers",
|
1116 |
+
"outmanoeuvring": "outmaneuvering",
|
1117 |
+
"overemphasise": "overemphasize",
|
1118 |
+
"overemphasised": "overemphasized",
|
1119 |
+
"overemphasises": "overemphasizes",
|
1120 |
+
"overemphasising": "overemphasizing",
|
1121 |
+
"oxidisation": "oxidization",
|
1122 |
+
"oxidise": "oxidize",
|
1123 |
+
"oxidised": "oxidized",
|
1124 |
+
"oxidises": "oxidizes",
|
1125 |
+
"oxidising": "oxidizing",
|
1126 |
+
"paederast": "pederast",
|
1127 |
+
"paederasts": "pederasts",
|
1128 |
+
"paediatric": "pediatric",
|
1129 |
+
"paediatrician": "pediatrician",
|
1130 |
+
"paediatricians": "pediatricians",
|
1131 |
+
"paediatrics": "pediatrics",
|
1132 |
+
"paedophile": "pedophile",
|
1133 |
+
"paedophiles": "pedophiles",
|
1134 |
+
"paedophilia": "pedophilia",
|
1135 |
+
"palaeolithic": "paleolithic",
|
1136 |
+
"palaeontologist": "paleontologist",
|
1137 |
+
"palaeontologists": "paleontologists",
|
1138 |
+
"palaeontology": "paleontology",
|
1139 |
+
"panelled": "paneled",
|
1140 |
+
"panelling": "paneling",
|
1141 |
+
"panellist": "panelist",
|
1142 |
+
"panellists": "panelists",
|
1143 |
+
"paralyse": "paralyze",
|
1144 |
+
"paralysed": "paralyzed",
|
1145 |
+
"paralyses": "paralyzes",
|
1146 |
+
"paralysing": "paralyzing",
|
1147 |
+
"parcelled": "parceled",
|
1148 |
+
"parcelling": "parceling",
|
1149 |
+
"parlour": "parlor",
|
1150 |
+
"parlours": "parlors",
|
1151 |
+
"particularise": "particularize",
|
1152 |
+
"particularised": "particularized",
|
1153 |
+
"particularises": "particularizes",
|
1154 |
+
"particularising": "particularizing",
|
1155 |
+
"passivisation": "passivization",
|
1156 |
+
"passivise": "passivize",
|
1157 |
+
"passivised": "passivized",
|
1158 |
+
"passivises": "passivizes",
|
1159 |
+
"passivising": "passivizing",
|
1160 |
+
"pasteurisation": "pasteurization",
|
1161 |
+
"pasteurise": "pasteurize",
|
1162 |
+
"pasteurised": "pasteurized",
|
1163 |
+
"pasteurises": "pasteurizes",
|
1164 |
+
"pasteurising": "pasteurizing",
|
1165 |
+
"patronise": "patronize",
|
1166 |
+
"patronised": "patronized",
|
1167 |
+
"patronises": "patronizes",
|
1168 |
+
"patronising": "patronizing",
|
1169 |
+
"patronisingly": "patronizingly",
|
1170 |
+
"pedalled": "pedaled",
|
1171 |
+
"pedalling": "pedaling",
|
1172 |
+
"pedestrianisation": "pedestrianization",
|
1173 |
+
"pedestrianise": "pedestrianize",
|
1174 |
+
"pedestrianised": "pedestrianized",
|
1175 |
+
"pedestrianises": "pedestrianizes",
|
1176 |
+
"pedestrianising": "pedestrianizing",
|
1177 |
+
"penalise": "penalize",
|
1178 |
+
"penalised": "penalized",
|
1179 |
+
"penalises": "penalizes",
|
1180 |
+
"penalising": "penalizing",
|
1181 |
+
"pencilled": "penciled",
|
1182 |
+
"pencilling": "penciling",
|
1183 |
+
"personalise": "personalize",
|
1184 |
+
"personalised": "personalized",
|
1185 |
+
"personalises": "personalizes",
|
1186 |
+
"personalising": "personalizing",
|
1187 |
+
"pharmacopoeia": "pharmacopeia",
|
1188 |
+
"pharmacopoeias": "pharmacopeias",
|
1189 |
+
"philosophise": "philosophize",
|
1190 |
+
"philosophised": "philosophized",
|
1191 |
+
"philosophises": "philosophizes",
|
1192 |
+
"philosophising": "philosophizing",
|
1193 |
+
"philtre": "filter",
|
1194 |
+
"philtres": "filters",
|
1195 |
+
"phoney": "phony",
|
1196 |
+
"plagiarise": "plagiarize",
|
1197 |
+
"plagiarised": "plagiarized",
|
1198 |
+
"plagiarises": "plagiarizes",
|
1199 |
+
"plagiarising": "plagiarizing",
|
1200 |
+
"plough": "plow",
|
1201 |
+
"ploughed": "plowed",
|
1202 |
+
"ploughing": "plowing",
|
1203 |
+
"ploughman": "plowman",
|
1204 |
+
"ploughmen": "plowmen",
|
1205 |
+
"ploughs": "plows",
|
1206 |
+
"ploughshare": "plowshare",
|
1207 |
+
"ploughshares": "plowshares",
|
1208 |
+
"polarisation": "polarization",
|
1209 |
+
"polarise": "polarize",
|
1210 |
+
"polarised": "polarized",
|
1211 |
+
"polarises": "polarizes",
|
1212 |
+
"polarising": "polarizing",
|
1213 |
+
"politicisation": "politicization",
|
1214 |
+
"politicise": "politicize",
|
1215 |
+
"politicised": "politicized",
|
1216 |
+
"politicises": "politicizes",
|
1217 |
+
"politicising": "politicizing",
|
1218 |
+
"popularisation": "popularization",
|
1219 |
+
"popularise": "popularize",
|
1220 |
+
"popularised": "popularized",
|
1221 |
+
"popularises": "popularizes",
|
1222 |
+
"popularising": "popularizing",
|
1223 |
+
"pouffe": "pouf",
|
1224 |
+
"pouffes": "poufs",
|
1225 |
+
"practise": "practice",
|
1226 |
+
"practised": "practiced",
|
1227 |
+
"practises": "practices",
|
1228 |
+
"practising": "practicing",
|
1229 |
+
"praesidium": "presidium",
|
1230 |
+
"praesidiums": "presidiums",
|
1231 |
+
"pressurisation": "pressurization",
|
1232 |
+
"pressurise": "pressurize",
|
1233 |
+
"pressurised": "pressurized",
|
1234 |
+
"pressurises": "pressurizes",
|
1235 |
+
"pressurising": "pressurizing",
|
1236 |
+
"pretence": "pretense",
|
1237 |
+
"pretences": "pretenses",
|
1238 |
+
"primaeval": "primeval",
|
1239 |
+
"prioritisation": "prioritization",
|
1240 |
+
"prioritise": "prioritize",
|
1241 |
+
"prioritised": "prioritized",
|
1242 |
+
"prioritises": "prioritizes",
|
1243 |
+
"prioritising": "prioritizing",
|
1244 |
+
"privatisation": "privatization",
|
1245 |
+
"privatisations": "privatizations",
|
1246 |
+
"privatise": "privatize",
|
1247 |
+
"privatised": "privatized",
|
1248 |
+
"privatises": "privatizes",
|
1249 |
+
"privatising": "privatizing",
|
1250 |
+
"professionalisation": "professionalization",
|
1251 |
+
"professionalise": "professionalize",
|
1252 |
+
"professionalised": "professionalized",
|
1253 |
+
"professionalises": "professionalizes",
|
1254 |
+
"professionalising": "professionalizing",
|
1255 |
+
"programme": "program",
|
1256 |
+
"programmes": "programs",
|
1257 |
+
"prologue": "prolog",
|
1258 |
+
"prologues": "prologs",
|
1259 |
+
"propagandise": "propagandize",
|
1260 |
+
"propagandised": "propagandized",
|
1261 |
+
"propagandises": "propagandizes",
|
1262 |
+
"propagandising": "propagandizing",
|
1263 |
+
"proselytise": "proselytize",
|
1264 |
+
"proselytised": "proselytized",
|
1265 |
+
"proselytiser": "proselytizer",
|
1266 |
+
"proselytisers": "proselytizers",
|
1267 |
+
"proselytises": "proselytizes",
|
1268 |
+
"proselytising": "proselytizing",
|
1269 |
+
"psychoanalyse": "psychoanalyze",
|
1270 |
+
"psychoanalysed": "psychoanalyzed",
|
1271 |
+
"psychoanalyses": "psychoanalyzes",
|
1272 |
+
"psychoanalysing": "psychoanalyzing",
|
1273 |
+
"publicise": "publicize",
|
1274 |
+
"publicised": "publicized",
|
1275 |
+
"publicises": "publicizes",
|
1276 |
+
"publicising": "publicizing",
|
1277 |
+
"pulverisation": "pulverization",
|
1278 |
+
"pulverise": "pulverize",
|
1279 |
+
"pulverised": "pulverized",
|
1280 |
+
"pulverises": "pulverizes",
|
1281 |
+
"pulverising": "pulverizing",
|
1282 |
+
"pummelled": "pummel",
|
1283 |
+
"pummelling": "pummeled",
|
1284 |
+
"pyjama": "pajama",
|
1285 |
+
"pyjamas": "pajamas",
|
1286 |
+
"pzazz": "pizzazz",
|
1287 |
+
"quarrelled": "quarreled",
|
1288 |
+
"quarrelling": "quarreling",
|
1289 |
+
"radicalise": "radicalize",
|
1290 |
+
"radicalised": "radicalized",
|
1291 |
+
"radicalises": "radicalizes",
|
1292 |
+
"radicalising": "radicalizing",
|
1293 |
+
"rancour": "rancor",
|
1294 |
+
"randomise": "randomize",
|
1295 |
+
"randomised": "randomized",
|
1296 |
+
"randomises": "randomizes",
|
1297 |
+
"randomising": "randomizing",
|
1298 |
+
"rationalisation": "rationalization",
|
1299 |
+
"rationalisations": "rationalizations",
|
1300 |
+
"rationalise": "rationalize",
|
1301 |
+
"rationalised": "rationalized",
|
1302 |
+
"rationalises": "rationalizes",
|
1303 |
+
"rationalising": "rationalizing",
|
1304 |
+
"ravelled": "raveled",
|
1305 |
+
"ravelling": "raveling",
|
1306 |
+
"realisable": "realizable",
|
1307 |
+
"realisation": "realization",
|
1308 |
+
"realisations": "realizations",
|
1309 |
+
"realise": "realize",
|
1310 |
+
"realised": "realized",
|
1311 |
+
"realises": "realizes",
|
1312 |
+
"realising": "realizing",
|
1313 |
+
"recognisable": "recognizable",
|
1314 |
+
"recognisably": "recognizably",
|
1315 |
+
"recognisance": "recognizance",
|
1316 |
+
"recognise": "recognize",
|
1317 |
+
"recognised": "recognized",
|
1318 |
+
"recognises": "recognizes",
|
1319 |
+
"recognising": "recognizing",
|
1320 |
+
"reconnoitre": "reconnoiter",
|
1321 |
+
"reconnoitred": "reconnoitered",
|
1322 |
+
"reconnoitres": "reconnoiters",
|
1323 |
+
"reconnoitring": "reconnoitering",
|
1324 |
+
"refuelled": "refueled",
|
1325 |
+
"refuelling": "refueling",
|
1326 |
+
"regularisation": "regularization",
|
1327 |
+
"regularise": "regularize",
|
1328 |
+
"regularised": "regularized",
|
1329 |
+
"regularises": "regularizes",
|
1330 |
+
"regularising": "regularizing",
|
1331 |
+
"remodelled": "remodeled",
|
1332 |
+
"remodelling": "remodeling",
|
1333 |
+
"remould": "remold",
|
1334 |
+
"remoulded": "remolded",
|
1335 |
+
"remoulding": "remolding",
|
1336 |
+
"remoulds": "remolds",
|
1337 |
+
"reorganisation": "reorganization",
|
1338 |
+
"reorganisations": "reorganizations",
|
1339 |
+
"reorganise": "reorganize",
|
1340 |
+
"reorganised": "reorganized",
|
1341 |
+
"reorganises": "reorganizes",
|
1342 |
+
"reorganising": "reorganizing",
|
1343 |
+
"revelled": "reveled",
|
1344 |
+
"reveller": "reveler",
|
1345 |
+
"revellers": "revelers",
|
1346 |
+
"revelling": "reveling",
|
1347 |
+
"revitalise": "revitalize",
|
1348 |
+
"revitalised": "revitalized",
|
1349 |
+
"revitalises": "revitalizes",
|
1350 |
+
"revitalising": "revitalizing",
|
1351 |
+
"revolutionise": "revolutionize",
|
1352 |
+
"revolutionised": "revolutionized",
|
1353 |
+
"revolutionises": "revolutionizes",
|
1354 |
+
"revolutionising": "revolutionizing",
|
1355 |
+
"rhapsodise": "rhapsodize",
|
1356 |
+
"rhapsodised": "rhapsodized",
|
1357 |
+
"rhapsodises": "rhapsodizes",
|
1358 |
+
"rhapsodising": "rhapsodizing",
|
1359 |
+
"rigour": "rigor",
|
1360 |
+
"rigours": "rigors",
|
1361 |
+
"ritualised": "ritualized",
|
1362 |
+
"rivalled": "rivaled",
|
1363 |
+
"rivalling": "rivaling",
|
1364 |
+
"romanticise": "romanticize",
|
1365 |
+
"romanticised": "romanticized",
|
1366 |
+
"romanticises": "romanticizes",
|
1367 |
+
"romanticising": "romanticizing",
|
1368 |
+
"rumour": "rumor",
|
1369 |
+
"rumoured": "rumored",
|
1370 |
+
"rumours": "rumors",
|
1371 |
+
"sabre": "saber",
|
1372 |
+
"sabres": "sabers",
|
1373 |
+
"saltpetre": "saltpeter",
|
1374 |
+
"sanitise": "sanitize",
|
1375 |
+
"sanitised": "sanitized",
|
1376 |
+
"sanitises": "sanitizes",
|
1377 |
+
"sanitising": "sanitizing",
|
1378 |
+
"satirise": "satirize",
|
1379 |
+
"satirised": "satirized",
|
1380 |
+
"satirises": "satirizes",
|
1381 |
+
"satirising": "satirizing",
|
1382 |
+
"saviour": "savior",
|
1383 |
+
"saviours": "saviors",
|
1384 |
+
"savour": "savor",
|
1385 |
+
"savoured": "savored",
|
1386 |
+
"savouries": "savories",
|
1387 |
+
"savouring": "savoring",
|
1388 |
+
"savours": "savors",
|
1389 |
+
"savoury": "savory",
|
1390 |
+
"scandalise": "scandalize",
|
1391 |
+
"scandalised": "scandalized",
|
1392 |
+
"scandalises": "scandalizes",
|
1393 |
+
"scandalising": "scandalizing",
|
1394 |
+
"sceptic": "skeptic",
|
1395 |
+
"sceptical": "skeptical",
|
1396 |
+
"sceptically": "skeptically",
|
1397 |
+
"scepticism": "skepticism",
|
1398 |
+
"sceptics": "skeptics",
|
1399 |
+
"sceptre": "scepter",
|
1400 |
+
"sceptres": "scepters",
|
1401 |
+
"scrutinise": "scrutinize",
|
1402 |
+
"scrutinised": "scrutinized",
|
1403 |
+
"scrutinises": "scrutinizes",
|
1404 |
+
"scrutinising": "scrutinizing",
|
1405 |
+
"secularisation": "secularization",
|
1406 |
+
"secularise": "secularize",
|
1407 |
+
"secularised": "secularized",
|
1408 |
+
"secularises": "secularizes",
|
1409 |
+
"secularising": "secularizing",
|
1410 |
+
"sensationalise": "sensationalize",
|
1411 |
+
"sensationalised": "sensationalized",
|
1412 |
+
"sensationalises": "sensationalizes",
|
1413 |
+
"sensationalising": "sensationalizing",
|
1414 |
+
"sensitise": "sensitize",
|
1415 |
+
"sensitised": "sensitized",
|
1416 |
+
"sensitises": "sensitizes",
|
1417 |
+
"sensitising": "sensitizing",
|
1418 |
+
"sentimentalise": "sentimentalize",
|
1419 |
+
"sentimentalised": "sentimentalized",
|
1420 |
+
"sentimentalises": "sentimentalizes",
|
1421 |
+
"sentimentalising": "sentimentalizing",
|
1422 |
+
"sepulchre": "sepulcher",
|
1423 |
+
"sepulchres": "sepulchers",
|
1424 |
+
"serialisation": "serialization",
|
1425 |
+
"serialisations": "serializations",
|
1426 |
+
"serialise": "serialize",
|
1427 |
+
"serialised": "serialized",
|
1428 |
+
"serialises": "serializes",
|
1429 |
+
"serialising": "serializing",
|
1430 |
+
"sermonise": "sermonize",
|
1431 |
+
"sermonised": "sermonized",
|
1432 |
+
"sermonises": "sermonizes",
|
1433 |
+
"sermonising": "sermonizing",
|
1434 |
+
"sheikh": "sheik",
|
1435 |
+
"shovelled": "shoveled",
|
1436 |
+
"shovelling": "shoveling",
|
1437 |
+
"shrivelled": "shriveled",
|
1438 |
+
"shrivelling": "shriveling",
|
1439 |
+
"signalise": "signalize",
|
1440 |
+
"signalised": "signalized",
|
1441 |
+
"signalises": "signalizes",
|
1442 |
+
"signalising": "signalizing",
|
1443 |
+
"signalled": "signaled",
|
1444 |
+
"signalling": "signaling",
|
1445 |
+
"smoulder": "smolder",
|
1446 |
+
"smouldered": "smoldered",
|
1447 |
+
"smouldering": "smoldering",
|
1448 |
+
"smoulders": "smolders",
|
1449 |
+
"snivelled": "sniveled",
|
1450 |
+
"snivelling": "sniveling",
|
1451 |
+
"snorkelled": "snorkeled",
|
1452 |
+
"snorkelling": "snorkeling",
|
1453 |
+
"snowplough": "snowplow",
|
1454 |
+
"snowploughs": "snowplow",
|
1455 |
+
"socialisation": "socialization",
|
1456 |
+
"socialise": "socialize",
|
1457 |
+
"socialised": "socialized",
|
1458 |
+
"socialises": "socializes",
|
1459 |
+
"socialising": "socializing",
|
1460 |
+
"sodomise": "sodomize",
|
1461 |
+
"sodomised": "sodomized",
|
1462 |
+
"sodomises": "sodomizes",
|
1463 |
+
"sodomising": "sodomizing",
|
1464 |
+
"solemnise": "solemnize",
|
1465 |
+
"solemnised": "solemnized",
|
1466 |
+
"solemnises": "solemnizes",
|
1467 |
+
"solemnising": "solemnizing",
|
1468 |
+
"sombre": "somber",
|
1469 |
+
"specialisation": "specialization",
|
1470 |
+
"specialisations": "specializations",
|
1471 |
+
"specialise": "specialize",
|
1472 |
+
"specialised": "specialized",
|
1473 |
+
"specialises": "specializes",
|
1474 |
+
"specialising": "specializing",
|
1475 |
+
"spectre": "specter",
|
1476 |
+
"spectres": "specters",
|
1477 |
+
"spiralled": "spiraled",
|
1478 |
+
"spiralling": "spiraling",
|
1479 |
+
"splendour": "splendor",
|
1480 |
+
"splendours": "splendors",
|
1481 |
+
"squirrelled": "squirreled",
|
1482 |
+
"squirrelling": "squirreling",
|
1483 |
+
"stabilisation": "stabilization",
|
1484 |
+
"stabilise": "stabilize",
|
1485 |
+
"stabilised": "stabilized",
|
1486 |
+
"stabiliser": "stabilizer",
|
1487 |
+
"stabilisers": "stabilizers",
|
1488 |
+
"stabilises": "stabilizes",
|
1489 |
+
"stabilising": "stabilizing",
|
1490 |
+
"standardisation": "standardization",
|
1491 |
+
"standardise": "standardize",
|
1492 |
+
"standardised": "standardized",
|
1493 |
+
"standardises": "standardizes",
|
1494 |
+
"standardising": "standardizing",
|
1495 |
+
"stencilled": "stenciled",
|
1496 |
+
"stencilling": "stenciling",
|
1497 |
+
"sterilisation": "sterilization",
|
1498 |
+
"sterilisations": "sterilizations",
|
1499 |
+
"sterilise": "sterilize",
|
1500 |
+
"sterilised": "sterilized",
|
1501 |
+
"steriliser": "sterilizer",
|
1502 |
+
"sterilisers": "sterilizers",
|
1503 |
+
"sterilises": "sterilizes",
|
1504 |
+
"sterilising": "sterilizing",
|
1505 |
+
"stigmatisation": "stigmatization",
|
1506 |
+
"stigmatise": "stigmatize",
|
1507 |
+
"stigmatised": "stigmatized",
|
1508 |
+
"stigmatises": "stigmatizes",
|
1509 |
+
"stigmatising": "stigmatizing",
|
1510 |
+
"storey": "story",
|
1511 |
+
"storeys": "stories",
|
1512 |
+
"subsidisation": "subsidization",
|
1513 |
+
"subsidise": "subsidize",
|
1514 |
+
"subsidised": "subsidized",
|
1515 |
+
"subsidiser": "subsidizer",
|
1516 |
+
"subsidisers": "subsidizers",
|
1517 |
+
"subsidises": "subsidizes",
|
1518 |
+
"subsidising": "subsidizing",
|
1519 |
+
"succour": "succor",
|
1520 |
+
"succoured": "succored",
|
1521 |
+
"succouring": "succoring",
|
1522 |
+
"succours": "succors",
|
1523 |
+
"sulphate": "sulfate",
|
1524 |
+
"sulphates": "sulfates",
|
1525 |
+
"sulphide": "sulfide",
|
1526 |
+
"sulphides": "sulfides",
|
1527 |
+
"sulphur": "sulfur",
|
1528 |
+
"sulphurous": "sulfurous",
|
1529 |
+
"summarise": "summarize",
|
1530 |
+
"summarised": "summarized",
|
1531 |
+
"summarises": "summarizes",
|
1532 |
+
"summarising": "summarizing",
|
1533 |
+
"swivelled": "swiveled",
|
1534 |
+
"swivelling": "swiveling",
|
1535 |
+
"symbolise": "symbolize",
|
1536 |
+
"symbolised": "symbolized",
|
1537 |
+
"symbolises": "symbolizes",
|
1538 |
+
"symbolising": "symbolizing",
|
1539 |
+
"sympathise": "sympathize",
|
1540 |
+
"sympathised": "sympathized",
|
1541 |
+
"sympathiser": "sympathizer",
|
1542 |
+
"sympathisers": "sympathizers",
|
1543 |
+
"sympathises": "sympathizes",
|
1544 |
+
"sympathising": "sympathizing",
|
1545 |
+
"synchronisation": "synchronization",
|
1546 |
+
"synchronise": "synchronize",
|
1547 |
+
"synchronised": "synchronized",
|
1548 |
+
"synchronises": "synchronizes",
|
1549 |
+
"synchronising": "synchronizing",
|
1550 |
+
"synthesise": "synthesize",
|
1551 |
+
"synthesised": "synthesized",
|
1552 |
+
"synthesiser": "synthesizer",
|
1553 |
+
"synthesisers": "synthesizers",
|
1554 |
+
"synthesises": "synthesizes",
|
1555 |
+
"synthesising": "synthesizing",
|
1556 |
+
"syphon": "siphon",
|
1557 |
+
"syphoned": "siphoned",
|
1558 |
+
"syphoning": "siphoning",
|
1559 |
+
"syphons": "siphons",
|
1560 |
+
"systematisation": "systematization",
|
1561 |
+
"systematise": "systematize",
|
1562 |
+
"systematised": "systematized",
|
1563 |
+
"systematises": "systematizes",
|
1564 |
+
"systematising": "systematizing",
|
1565 |
+
"tantalise": "tantalize",
|
1566 |
+
"tantalised": "tantalized",
|
1567 |
+
"tantalises": "tantalizes",
|
1568 |
+
"tantalising": "tantalizing",
|
1569 |
+
"tantalisingly": "tantalizingly",
|
1570 |
+
"tasselled": "tasseled",
|
1571 |
+
"technicolour": "technicolor",
|
1572 |
+
"temporise": "temporize",
|
1573 |
+
"temporised": "temporized",
|
1574 |
+
"temporises": "temporizes",
|
1575 |
+
"temporising": "temporizing",
|
1576 |
+
"tenderise": "tenderize",
|
1577 |
+
"tenderised": "tenderized",
|
1578 |
+
"tenderises": "tenderizes",
|
1579 |
+
"tenderising": "tenderizing",
|
1580 |
+
"terrorise": "terrorize",
|
1581 |
+
"terrorised": "terrorized",
|
1582 |
+
"terrorises": "terrorizes",
|
1583 |
+
"terrorising": "terrorizing",
|
1584 |
+
"theatre": "theater",
|
1585 |
+
"theatregoer": "theatergoer",
|
1586 |
+
"theatregoers": "theatergoers",
|
1587 |
+
"theatres": "theaters",
|
1588 |
+
"theorise": "theorize",
|
1589 |
+
"theorised": "theorized",
|
1590 |
+
"theorises": "theorizes",
|
1591 |
+
"theorising": "theorizing",
|
1592 |
+
"tonne": "ton",
|
1593 |
+
"tonnes": "tons",
|
1594 |
+
"towelled": "toweled",
|
1595 |
+
"towelling": "toweling",
|
1596 |
+
"toxaemia": "toxemia",
|
1597 |
+
"tranquillise": "tranquilize",
|
1598 |
+
"tranquillised": "tranquilized",
|
1599 |
+
"tranquilliser": "tranquilizer",
|
1600 |
+
"tranquillisers": "tranquilizers",
|
1601 |
+
"tranquillises": "tranquilizes",
|
1602 |
+
"tranquillising": "tranquilizing",
|
1603 |
+
"tranquillity": "tranquility",
|
1604 |
+
"tranquillize": "tranquilize",
|
1605 |
+
"tranquillized": "tranquilized",
|
1606 |
+
"tranquillizer": "tranquilizer",
|
1607 |
+
"tranquillizers": "tranquilizers",
|
1608 |
+
"tranquillizes": "tranquilizes",
|
1609 |
+
"tranquillizing": "tranquilizing",
|
1610 |
+
"tranquilly": "tranquility",
|
1611 |
+
"transistorised": "transistorized",
|
1612 |
+
"traumatise": "traumatize",
|
1613 |
+
"traumatised": "traumatized",
|
1614 |
+
"traumatises": "traumatizes",
|
1615 |
+
"traumatising": "traumatizing",
|
1616 |
+
"travelled": "traveled",
|
1617 |
+
"traveller": "traveler",
|
1618 |
+
"travellers": "travelers",
|
1619 |
+
"travelling": "traveling",
|
1620 |
+
"travelog": "travelogue",
|
1621 |
+
"travelogs": "travelogues",
|
1622 |
+
"trialled": "trialed",
|
1623 |
+
"trialling": "trialing",
|
1624 |
+
"tricolour": "tricolor",
|
1625 |
+
"tricolours": "tricolors",
|
1626 |
+
"trivialise": "trivialize",
|
1627 |
+
"trivialised": "trivialized",
|
1628 |
+
"trivialises": "trivializes",
|
1629 |
+
"trivialising": "trivializing",
|
1630 |
+
"tumour": "tumor",
|
1631 |
+
"tumours": "tumors",
|
1632 |
+
"tunnelled": "tunneled",
|
1633 |
+
"tunnelling": "tunneling",
|
1634 |
+
"tyrannise": "tyrannize",
|
1635 |
+
"tyrannised": "tyrannized",
|
1636 |
+
"tyrannises": "tyrannizes",
|
1637 |
+
"tyrannising": "tyrannizing",
|
1638 |
+
"tyre": "tire",
|
1639 |
+
"tyres": "tires",
|
1640 |
+
"unauthorised": "unauthorized",
|
1641 |
+
"uncivilised": "uncivilized",
|
1642 |
+
"underutilised": "underutilized",
|
1643 |
+
"unequalled": "unequaled",
|
1644 |
+
"unfavourable": "unfavorable",
|
1645 |
+
"unfavourably": "unfavorably",
|
1646 |
+
"unionisation": "unionization",
|
1647 |
+
"unionise": "unionize",
|
1648 |
+
"unionised": "unionized",
|
1649 |
+
"unionises": "unionizes",
|
1650 |
+
"unionising": "unionizing",
|
1651 |
+
"unorganised": "unorganized",
|
1652 |
+
"unravelled": "unraveled",
|
1653 |
+
"unravelling": "unraveling",
|
1654 |
+
"unrecognisable": "unrecognizable",
|
1655 |
+
"unrecognised": "unrecognized",
|
1656 |
+
"unrivalled": "unrivaled",
|
1657 |
+
"unsavoury": "unsavory",
|
1658 |
+
"untrammelled": "untrammeled",
|
1659 |
+
"urbanisation": "urbanization",
|
1660 |
+
"urbanise": "urbanize",
|
1661 |
+
"urbanised": "urbanized",
|
1662 |
+
"urbanises": "urbanizes",
|
1663 |
+
"urbanising": "urbanizing",
|
1664 |
+
"utilisable": "utilizable",
|
1665 |
+
"utilisation": "utilization",
|
1666 |
+
"utilise": "utilize",
|
1667 |
+
"utilised": "utilized",
|
1668 |
+
"utilises": "utilizes",
|
1669 |
+
"utilising": "utilizing",
|
1670 |
+
"valour": "valor",
|
1671 |
+
"vandalise": "vandalize",
|
1672 |
+
"vandalised": "vandalized",
|
1673 |
+
"vandalises": "vandalizes",
|
1674 |
+
"vandalising": "vandalizing",
|
1675 |
+
"vaporisation": "vaporization",
|
1676 |
+
"vaporise": "vaporize",
|
1677 |
+
"vaporised": "vaporized",
|
1678 |
+
"vaporises": "vaporizes",
|
1679 |
+
"vaporising": "vaporizing",
|
1680 |
+
"vapour": "vapor",
|
1681 |
+
"vapours": "vapors",
|
1682 |
+
"verbalise": "verbalize",
|
1683 |
+
"verbalised": "verbalized",
|
1684 |
+
"verbalises": "verbalizes",
|
1685 |
+
"verbalising": "verbalizing",
|
1686 |
+
"victimisation": "victimization",
|
1687 |
+
"victimise": "victimize",
|
1688 |
+
"victimised": "victimized",
|
1689 |
+
"victimises": "victimizes",
|
1690 |
+
"victimising": "victimizing",
|
1691 |
+
"videodisc": "videodisk",
|
1692 |
+
"videodiscs": "videodisks",
|
1693 |
+
"vigour": "vigor",
|
1694 |
+
"visualisation": "visualization",
|
1695 |
+
"visualisations": "visualizations",
|
1696 |
+
"visualise": "visualize",
|
1697 |
+
"visualised": "visualized",
|
1698 |
+
"visualises": "visualizes",
|
1699 |
+
"visualising": "visualizing",
|
1700 |
+
"vocalisation": "vocalization",
|
1701 |
+
"vocalisations": "vocalizations",
|
1702 |
+
"vocalise": "vocalize",
|
1703 |
+
"vocalised": "vocalized",
|
1704 |
+
"vocalises": "vocalizes",
|
1705 |
+
"vocalising": "vocalizing",
|
1706 |
+
"vulcanised": "vulcanized",
|
1707 |
+
"vulgarisation": "vulgarization",
|
1708 |
+
"vulgarise": "vulgarize",
|
1709 |
+
"vulgarised": "vulgarized",
|
1710 |
+
"vulgarises": "vulgarizes",
|
1711 |
+
"vulgarising": "vulgarizing",
|
1712 |
+
"waggon": "wagon",
|
1713 |
+
"waggons": "wagons",
|
1714 |
+
"watercolour": "watercolor",
|
1715 |
+
"watercolours": "watercolors",
|
1716 |
+
"weaselled": "weaseled",
|
1717 |
+
"weaselling": "weaseling",
|
1718 |
+
"westernisation": "westernization",
|
1719 |
+
"westernise": "westernize",
|
1720 |
+
"westernised": "westernized",
|
1721 |
+
"westernises": "westernizes",
|
1722 |
+
"westernising": "westernizing",
|
1723 |
+
"womanise": "womanize",
|
1724 |
+
"womanised": "womanized",
|
1725 |
+
"womaniser": "womanizer",
|
1726 |
+
"womanisers": "womanizers",
|
1727 |
+
"womanises": "womanizes",
|
1728 |
+
"womanising": "womanizing",
|
1729 |
+
"woollen": "woolen",
|
1730 |
+
"woollens": "woolens",
|
1731 |
+
"woollies": "woolies",
|
1732 |
+
"woolly": "wooly",
|
1733 |
+
"worshipped": "worshiped",
|
1734 |
+
"worshipper": "worshiper",
|
1735 |
+
"worshipping": "worshiping",
|
1736 |
+
"yodelled": "yodeled",
|
1737 |
+
"yodelling": "yodeling",
|
1738 |
+
"yoghourt": "yogurt",
|
1739 |
+
"yoghourts": "yogurts",
|
1740 |
+
"yoghurt": "yogurt",
|
1741 |
+
"yoghurts": "yogurts"
|
1742 |
+
}
|
preprocessor_config.json
ADDED
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"chunk_length": 30,
|
3 |
+
"feature_extractor_type": "WhisperFeatureExtractor",
|
4 |
+
"feature_size": 80,
|
5 |
+
"hop_length": 160,
|
6 |
+
"n_fft": 400,
|
7 |
+
"n_samples": 480000,
|
8 |
+
"nb_max_frames": 3000,
|
9 |
+
"padding_side": "right",
|
10 |
+
"padding_value": 0.0,
|
11 |
+
"processor_class": "WhisperProcessor",
|
12 |
+
"return_attention_mask": false,
|
13 |
+
"sampling_rate": 16000
|
14 |
+
}
|
pytorch_model.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f8b7db43722c09d7b27c717393cd01d6cbbb0a0bfed84454c6a435e84f2c91e3
|
3 |
+
size 967102601
|
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+
{
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