Update README.md

README.md

@@ -1,173 +1,173 @@
----
-annotations_creators:
-- expert-generated
-- crowdsourced
-- machine-generated
-language_creators:
-- crowdsourced
-- expert-generated
-languages:
-- en
-- en-GB
-- en-US
-- en-AU
-- fr
-- it
-- es
-- pt
-- de
-- nl
-- ru
-- pl
-- cs
-- ko
-- zh
-licenses:
-- cc-by-4.0
-multilinguality:
-- multilingual
-pretty_name: 'MInDS-14'
-size_categories:
-- 10K<n<100K
-task_categories:
-- automatic-speech-recognition
-- speech-processing
-task_ids:
-- speech-recognition
----
-
-# MInDS-14
-
-## Dataset Description
-
-- **Fine-Tuning script:** [research-projects/xtreme-s](https://github.com/huggingface/transformers/tree/main/examples/pytorch/audio-classification)
-- **Paper:** [Multilingual and Cross-Lingual Intent Detection from Spoken Data](https://arxiv.org/abs/2104.08524)
-- **Total amount of disk used:** ca. 500 MB 
-
-MINDS-14 is training and evaluation resource for intent detection task with spoken data. It covers 14 
-intents extracted from a commercial system in the e-banking domain, associated with spoken examples in 14 diverse language varieties.
-
-## Example
-
-MInDS-14 can be downloaded and used as follows:
-
-```py
-from datasets import load_dataset
-
-minds_14 = load_dataset("PolyAI/minds14", "fr-FR") # for French
-# to download all data for multi-lingual fine-tuning uncomment following line
-# minds_14 = load_dataset("PolyAI/all", "all")
-
-# see structure
-print(minds_14)
-
-# load audio sample on the fly
-audio_input = minds_14["train"][0]["audio"]  # first decoded audio sample
-intent_class = minds_14["train"][0]["intent_class"]  # first transcription
-intent = minds_14["train"].features["intent_class"].names[intent_class]
-
-# use audio_input and language_class to fine-tune your model for audio classification
-```
-
-## Dataset Structure
-
-We show detailed information the example configurations `fr-FR` of the dataset.
-All other configurations have the same structure.
-
-### Data Instances
-
-**fr-FR**
-
-- Size of downloaded dataset files: 471 MB
-- Size of the generated dataset: 300 KB
-- Total amount of disk used: 471 MB
-
-
-An example of a datainstance of the config `fr-FR` looks as follows:
-
-```
-{
-    "path": "/home/patrick/.cache/huggingface/datasets/downloads/extracted/3ebe2265b2f102203be5e64fa8e533e0c6742e72268772c8ac1834c5a1a921e3/fr-FR~ADDRESS/response_4.wav",
-    "audio": {
-        "path": "/home/patrick/.cache/huggingface/datasets/downloads/extracted/3ebe2265b2f102203be5e64fa8e533e0c6742e72268772c8ac1834c5a1a921e3/fr-FR~ADDRESS/response_4.wav",
-        "array": array(
-            [0.0, 0.0, 0.0, ..., 0.0, 0.00048828, -0.00024414], dtype=float32
-        ),
-        "sampling_rate": 8000,
-    },
-    "transcription": "je souhaite changer mon adresse",
-    "english_transcription": "I want to change my address",
-    "intent_class": 1,
-    "lang_id": 6,
-}
-```
-
-### Data Fields
-The data fields are the same among all splits.
-
-- **path** (str): Path to the audio file
-- **audio** (dict): Audio object including loaded audio array, sampling rate and path ot audio
-- **transcription** (str): Transcription of the audio file
-- **english_transcription** (str): English transcription of the audio file
-- **intent_class** (int): Class id of intent
-- **lang_id** (int): Id of language
-
-### Data Splits
-Every config only has the `"train"` split containing of *ca.* 600 examples.
-
-## Dataset Creation
-
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Discussion of Biases
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Other Known Limitations
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Additional Information
-
-### Dataset Curators
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Licensing Information
-
-All datasets are licensed under the [Creative Commons license (CC-BY)](https://creativecommons.org/licenses/).
-
-### Citation Information
-
-```
-@article{DBLP:journals/corr/abs-2104-08524,
-  author    = {Daniela Gerz and
-               Pei{-}Hao Su and
-               Razvan Kusztos and
-               Avishek Mondal and
-               Michal Lis and
-               Eshan Singhal and
-               Nikola Mrksic and
-               Tsung{-}Hsien Wen and
-               Ivan Vulic},
-  title     = {Multilingual and Cross-Lingual Intent Detection from Spoken Data},
-  journal   = {CoRR},
-  volume    = {abs/2104.08524},
-  year      = {2021},
-  url       = {https://arxiv.org/abs/2104.08524},
-  eprinttype = {arXiv},
-  eprint    = {2104.08524},
-  timestamp = {Mon, 26 Apr 2021 17:25:10 +0200},
-  biburl    = {https://dblp.org/rec/journals/corr/abs-2104-08524.bib},
-  bibsource = {dblp computer science bibliography, https://dblp.org}
-}
-```
-
-### Contributions
-
-Thanks to [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset
+---
+annotations_creators:
+- expert-generated
+- crowdsourced
+- machine-generated
+language_creators:
+- crowdsourced
+- expert-generated
+languages:
+- en
+- en-GB
+- en-US
+- en-AU
+- fr
+- it
+- es
+- pt
+- de
+- nl
+- ru
+- pl
+- cs
+- ko
+- zh
+licenses:
+- cc-by-4.0
+multilinguality:
+- multilingual
+pretty_name: 'MInDS-14'
+size_categories:
+- 10K<n<100K
+task_categories:
+- automatic-speech-recognition
+- speech-processing
+task_ids:
+- speech-recognition
+---
+
+# MInDS-14
+
+## Dataset Description
+
+- **Fine-Tuning script:** [pytorch/audio-classification](https://github.com/huggingface/transformers/tree/main/examples/pytorch/audio-classification)
+- **Paper:** [Multilingual and Cross-Lingual Intent Detection from Spoken Data](https://arxiv.org/abs/2104.08524)
+- **Total amount of disk used:** ca. 500 MB 
+
+MINDS-14 is training and evaluation resource for intent detection task with spoken data. It covers 14 
+intents extracted from a commercial system in the e-banking domain, associated with spoken examples in 14 diverse language varieties.
+
+## Example
+
+MInDS-14 can be downloaded and used as follows:
+
+```py
+from datasets import load_dataset
+
+minds_14 = load_dataset("PolyAI/minds14", "fr-FR") # for French
+# to download all data for multi-lingual fine-tuning uncomment following line
+# minds_14 = load_dataset("PolyAI/all", "all")
+
+# see structure
+print(minds_14)
+
+# load audio sample on the fly
+audio_input = minds_14["train"][0]["audio"]  # first decoded audio sample
+intent_class = minds_14["train"][0]["intent_class"]  # first transcription
+intent = minds_14["train"].features["intent_class"].names[intent_class]
+
+# use audio_input and language_class to fine-tune your model for audio classification
+```
+
+## Dataset Structure
+
+We show detailed information the example configurations `fr-FR` of the dataset.
+All other configurations have the same structure.
+
+### Data Instances
+
+**fr-FR**
+
+- Size of downloaded dataset files: 471 MB
+- Size of the generated dataset: 300 KB
+- Total amount of disk used: 471 MB
+
+
+An example of a datainstance of the config `fr-FR` looks as follows:
+
+```
+{
+    "path": "/home/patrick/.cache/huggingface/datasets/downloads/extracted/3ebe2265b2f102203be5e64fa8e533e0c6742e72268772c8ac1834c5a1a921e3/fr-FR~ADDRESS/response_4.wav",
+    "audio": {
+        "path": "/home/patrick/.cache/huggingface/datasets/downloads/extracted/3ebe2265b2f102203be5e64fa8e533e0c6742e72268772c8ac1834c5a1a921e3/fr-FR~ADDRESS/response_4.wav",
+        "array": array(
+            [0.0, 0.0, 0.0, ..., 0.0, 0.00048828, -0.00024414], dtype=float32
+        ),
+        "sampling_rate": 8000,
+    },
+    "transcription": "je souhaite changer mon adresse",
+    "english_transcription": "I want to change my address",
+    "intent_class": 1,
+    "lang_id": 6,
+}
+```
+
+### Data Fields
+The data fields are the same among all splits.
+
+- **path** (str): Path to the audio file
+- **audio** (dict): Audio object including loaded audio array, sampling rate and path ot audio
+- **transcription** (str): Transcription of the audio file
+- **english_transcription** (str): English transcription of the audio file
+- **intent_class** (int): Class id of intent
+- **lang_id** (int): Id of language
+
+### Data Splits
+Every config only has the `"train"` split containing of *ca.* 600 examples.
+
+## Dataset Creation
+
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Discussion of Biases
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Other Known Limitations
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Licensing Information
+
+All datasets are licensed under the [Creative Commons license (CC-BY)](https://creativecommons.org/licenses/).
+
+### Citation Information
+
+```
+@article{DBLP:journals/corr/abs-2104-08524,
+  author    = {Daniela Gerz and
+               Pei{-}Hao Su and
+               Razvan Kusztos and
+               Avishek Mondal and
+               Michal Lis and
+               Eshan Singhal and
+               Nikola Mrksic and
+               Tsung{-}Hsien Wen and
+               Ivan Vulic},
+  title     = {Multilingual and Cross-Lingual Intent Detection from Spoken Data},
+  journal   = {CoRR},
+  volume    = {abs/2104.08524},
+  year      = {2021},
+  url       = {https://arxiv.org/abs/2104.08524},
+  eprinttype = {arXiv},
+  eprint    = {2104.08524},
+  timestamp = {Mon, 26 Apr 2021 17:25:10 +0200},
+  biburl    = {https://dblp.org/rec/journals/corr/abs-2104-08524.bib},
+  bibsource = {dblp computer science bibliography, https://dblp.org}
+}
+```
+
+### Contributions
+
+Thanks to [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset