jibo_kids_wavlm_aed_transformer / README.md

balaji1312

Update model

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	---
	tags:
	- espnet
	- audio
	- automatic-speech-recognition
	language:
	- en
	datasets:
	- jibo_kids
	license: cc-by-4.0
	---

	## ESPnet2 ASR model

	### `balaji1312/jibo_kids_wavlm_aed_transformer`

	This model was trained by using recipe in [espnet](https://github.com/espnet/espnet/).

	### Demo: How to use in ESPnet2

	Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html)
	if you haven't done that already.

	```bash
	cd espnet

	pip install -e .
	cd egs2/jibo_kids/asr1
	./run.sh --skip_data_prep false --skip_train true --download_model balaji1312/jibo_kids_wavlm_aed_transformer
	```

	<!-- Generated by scripts/utils/show_asr_result.sh -->
	# RESULTS
	## Environments
	- date: `Thu Jan 30 06:18:01 EST 2025`
	- python version: `3.9.19 (main, May 6 2024, 19:43:03) [GCC 11.2.0]`
	- espnet version: `espnet 202402`
	- pytorch version: `pytorch 2.4.0`
	- Git hash: `c46aa9a594ff83d52cbf61d84c5650325d1ce527`
	- Commit date: `Sun Oct 13 14:39:31 2024 -0400`

	## exp/asr_train_asr_wavlm_transformer_raw_en_bpe1024
	### WER

	\|dataset\|Snt\|Wrd\|Corr\|Sub\|Del\|Ins\|Err\|S.Err\|
	\|---\|---\|---\|---\|---\|---\|---\|---\|---\|
	\|decode_asr_asr_model_valid.acc.best/test\|1044\|3686\|56.1\|31.4\|12.5\|8.1\|52.0\|62.3\|

	### CER

	\|dataset\|Snt\|Wrd\|Corr\|Sub\|Del\|Ins\|Err\|S.Err\|
	\|---\|---\|---\|---\|---\|---\|---\|---\|---\|
	\|decode_asr_asr_model_valid.acc.best/test\|1044\|16215\|75.4\|8.1\|16.6\|9.4\|34.1\|62.3\|

	### TER

	\|dataset\|Snt\|Wrd\|Corr\|Sub\|Del\|Ins\|Err\|S.Err\|
	\|---\|---\|---\|---\|---\|---\|---\|---\|---\|
	\|decode_asr_asr_model_valid.acc.best/test\|1044\|5220\|64.5\|18.0\|17.5\|10.4\|45.9\|62.3\|

	## exp/asr_train_asr_wavlm_transformer_raw_en_bpe1024/decode_asr_asr_model_valid.acc.best
	### WER

	\|dataset\|Snt\|Wrd\|Corr\|Sub\|Del\|Ins\|Err\|S.Err\|
	\|---\|---\|---\|---\|---\|---\|---\|---\|---\|
	\|org/dev\|853\|2372\|59.8\|31.2\|8.9\|7.2\|47.3\|64.0\|

	### CER

	\|dataset\|Snt\|Wrd\|Corr\|Sub\|Del\|Ins\|Err\|S.Err\|
	\|---\|---\|---\|---\|---\|---\|---\|---\|---\|
	\|org/dev\|853\|9855\|78.3\|7.3\|14.3\|8.4\|30.1\|64.0\|

	### TER

	\|dataset\|Snt\|Wrd\|Corr\|Sub\|Del\|Ins\|Err\|S.Err\|
	\|---\|---\|---\|---\|---\|---\|---\|---\|---\|
	\|org/dev\|853\|3590\|68.2\|16.2\|15.6\|6.4\|38.3\|64.0\|

	## ASR config

	<details><summary>expand</summary>

	```
	config: conf/tuning/train_asr_wavlm_transformer.yaml
	print_config: false
	log_level: INFO
	drop_last_iter: false
	dry_run: false
	iterator_type: sequence
	valid_iterator_type: null
	output_dir: exp/asr_train_asr_wavlm_transformer_raw_en_bpe1024
	ngpu: 1
	seed: 2022
	num_workers: 4
	num_att_plot: 0
	dist_backend: nccl
	dist_init_method: env://
	dist_world_size: null
	dist_rank: null
	local_rank: 0
	dist_master_addr: null
	dist_master_port: null
	dist_launcher: null
	multiprocessing_distributed: false
	unused_parameters: false
	sharded_ddp: false
	use_deepspeed: false
	deepspeed_config: null
	cudnn_enabled: true
	cudnn_benchmark: false
	cudnn_deterministic: false
	use_tf32: false
	collect_stats: false
	write_collected_feats: false
	max_epoch: 100
	patience: null
	val_scheduler_criterion:
	- valid
	- loss
	early_stopping_criterion:
	- valid
	- loss
	- min
	best_model_criterion:
	- - valid
	- acc
	- max
	keep_nbest_models: 4
	nbest_averaging_interval: 0
	grad_clip: 5.0
	grad_clip_type: 2.0
	grad_noise: false
	accum_grad: 4
	no_forward_run: false
	resume: true
	train_dtype: float32
	use_amp: true
	log_interval: 400
	use_matplotlib: true
	use_tensorboard: true
	create_graph_in_tensorboard: false
	use_wandb: false
	wandb_project: null
	wandb_id: null
	wandb_entity: null
	wandb_name: null
	wandb_model_log_interval: -1
	detect_anomaly: false
	use_adapter: false
	adapter: lora
	save_strategy: all
	adapter_conf: {}
	pretrain_path: null
	init_param: []
	ignore_init_mismatch: false
	freeze_param:
	- frontend.upstream
	num_iters_per_epoch: null
	batch_size: 20
	valid_batch_size: null
	batch_bins: 1200000
	valid_batch_bins: null
	category_sample_size: 10
	train_shape_file:
	- exp/asr_stats_raw_en_bpe1024/train/speech_shape
	- exp/asr_stats_raw_en_bpe1024/train/text_shape.bpe
	valid_shape_file:
	- exp/asr_stats_raw_en_bpe1024/valid/speech_shape
	- exp/asr_stats_raw_en_bpe1024/valid/text_shape.bpe
	batch_type: numel
	valid_batch_type: null
	fold_length:
	- 80000
	- 150
	sort_in_batch: descending
	shuffle_within_batch: false
	sort_batch: descending
	multiple_iterator: false
	chunk_length: 500
	chunk_shift_ratio: 0.5
	num_cache_chunks: 1024
	chunk_excluded_key_prefixes: []
	chunk_default_fs: null
	chunk_max_abs_length: null
	chunk_discard_short_samples: true
	train_data_path_and_name_and_type:
	- - dump/raw/train/wav.scp
	- speech
	- sound
	- - dump/raw/train/text
	- text
	- text
	valid_data_path_and_name_and_type:
	- - dump/raw/dev/wav.scp
	- speech
	- sound
	- - dump/raw/dev/text
	- text
	- text
	multi_task_dataset: false
	allow_variable_data_keys: false
	max_cache_size: 0.0
	max_cache_fd: 32
	allow_multi_rates: false
	valid_max_cache_size: null
	exclude_weight_decay: false
	exclude_weight_decay_conf: {}
	optim: adam
	optim_conf:
	lr: 0.002
	weight_decay: 1.0e-06
	scheduler: warmuplr
	scheduler_conf:
	warmup_steps: 15000
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	- <unk>
	- .
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	- ▁AND
	- ''''
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	- G
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	- HIS
	- K
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	- AH
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	- U
	- AKING
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	- ▁GONNA
	- ▁FOUAH
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	- ▁KEEP
	- ES
	- P
	- ▁WAYS
	- TING
	- ALLY
	- VE
	- ONE
	- ▁QUESTION
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	- ▁STU
	- YTHING
	- ▁SHOW
	- ▁CALLED
	- ▁LOVE
	- ▁MM
	- ▁TRY
	- ▁BYE
	- ▁TOP
	- LD
	- ▁MMM
	- ▁PE
	- ▁NUMBERS
	- BLE
	- PLE
	- ▁CUBE
	- OUT
	- R
	- ▁BOTTOM
	- ▁FAVORITE
	- ▁SPANISH
	- ▁TONGUE
	- ▁SCHOOL
	- ▁TWENTY
	- ▁MHM
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	- ▁TEEF
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	- ▁GUM
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	- TY
	- ▁GROUPS
	- ▁OFF
	- ▁EQUALS
	- ▁FINGERS
	- ▁QUI
	- RAB
	- ▁MEANS
	- AW
	- ▁UHH
	- IT
	- WEE
	- ▁CH
	- ▁AM
	- ▁SI
	- RY
	- SIX
	- ▁WI
	- ▁BEAUTIFUL
	- ▁DENTIST
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	- ▁HURT
	- ▁ZEWO
	- ▁KNEW
	- ▁MATH
	- ▁BOY
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	- ▁YET
	- ▁EX
	- ▁STARTED
	- ▁LIGHT
	- ▁THESE
	- ▁CU
	- B
	- ▁THINGS
	- ▁GRA
	- ▁WHO
	- ▁TWOS
	- ▁CIRCLE
	- ▁YO
	- ▁FINGER
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	- CE
	- OTH
	- X
	- IR
	- MOST
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	- CI
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	- ▁DI
	- ▁HAPP
	- ▁DUH
	- OO
	- ▁JUH
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	- ▁HUH
	- ▁BUH
	- BOOK
	- WENT
	- ▁CA
	- OSE
	- EM
	- IC
	- AG
	- ▁LETTERS
	- IS
	- EW
	- ONG
	- V
	- AL
	- PAY
	- REE
	- EE
	- ▁TIMES
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	- UR
	- CU
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	- ▁TR
	- ▁AW
	- UGH
	- UT
	- ▁BL
	- ▁SL
	- ▁FORT
	- ▁GE
	- EA
	- ▁TA
	- GU
	- ▁FINISH
	- ▁UN
	- READ
	- THER
	- DAY
	- ▁BLA
	- ▁ARTIST
	- ▁BACKWARDS
	- ▁DOCTOR
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	- ▁EXPLA
	- ▁MIDDLE
	- ▁MOUSE
	- ▁PROB
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	- ▁STRAIGHT
	- ▁SUNFLOWER
	- ▁TOOTHPICK
	- ▁TWELVE
	- ▁VULTURE
	- ▁CONFUS
	- TION
	- ▁HOME
	- ▁OPEN
	- ▁SORRY
	- ▁BORING
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	- ▁FIN
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	- ▁BIVY
	- ▁BRACES
	- ▁FLOWER
	- ▁GARFIELD
	- ▁GARGLE
	- ▁KOALA
	- ▁PROBLEMS
	- ▁SEVENEIGHTNINE
	- ▁STINKY
	- ▁SWORD
	- ▁UPPERCASE
	- EMBER
	- FUL
	- ▁SEPARAT
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	- ▁BROKE
	- ▁LOUD
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	- ▁MOUF
	- ▁POOP
	- ▁SHINNY
	- ▁DRAW
	- ▁MAILBOX
	- ▁HUNGRY
	- ▁BREAK
	- ▁SARA
	- ▁JOB
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	- ▁LOOSE
	- ▁GREAT
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	- ACT
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	- ▁VEHA
	- ▁PEAR
	- ▁FEEL
	- ▁SPIDER
	- ▁WORSE
	- ▁SWI
	- ▁AYE
	- UNU
	- ▁EVER
	- ▁HOPE
	- ▁SIGN
	- AK
	- UIZ
	- ▁SOFT
	- ▁POP
	- ▁TEEH
	- ▁DEH
	- IBLE
	- ▁SIDEWAYS
	- ROT
	- ▁ORDER
	- ▁FINISHED
	- ▁JELLYFISH
	- ▁FELL
	- KEU
	- ▁IMPO
	- HEAD
	- UM
	- ▁PRESS
	- ▁SECONDS
	- ▁LEA
	- ▁MOLD
	- LLUH
	- ▁READ
	- ▁ONETWO
	- ▁LINE
	- FE
	- ▁FOH
	- ▁HOT
	- ▁FOU
	- ▁MOH
	- ▁DEN
	- ▁WIN
	- ▁NINETY
	- IRTY
	- ▁TWEE
	- OUR
	- IRED
	- TLE
	- ▁HEH
	- ▁JU
	- PASTE
	- ▁FEVER
	- ▁WR
	- ▁PAI
	- MINT
	- TEEN
	- ▁WASHING
	- ▁BI
	- ▁NAH
	- DY
	- ▁RA
	- ▁DA
	- AHW
	- ▁YUH
	- ULL
	- ▁WL
	- UHTY
	- ▁SHO
	- ▁CUH
	- ASTE
	- OOD
	- ▁LAM
	- ▁CI
	- OLD
	- UNN
	- NUH
	- OCK
	- US
	- ▁SM
	- MPLE
	- ▁HIT
	- ▁THRO
	- ▁DEU
	- HOLE
	- ▁THINKING
	- UBB
	- ▁FU
	- ▁PI
	- ▁SMO
	- ▁VO
	- AN
	- UG
	- ▁HM
	- UE
	- GLE
	- ▁MOV
	- LI
	- ▁BLU
	- PORT
	- ▁WED
	- ▁TRI
	- ▁CHE
	- CA
	- ▁SC
	- ▁STO
	- ▁BED
	- ▁TELLS
	- ▁MI
	- OR
	- TTER
	- NES
	- OUGH
	- ▁AR
	- ROW
	- UA
	- AB
	- IG
	- OF
	- MAN
	- RK
	- OUN
	- ROUGH
	- LUH
	- DENT
	- ▁PIE
	- LAP
	- KUH
	- OT
	- RSE
	- ▁LA
	- ▁PAST
	- ▁ANOTH
	- OP
	- EP
	- ▁LATE
	- AM
	- LU
	- ▁WOO
	- HUH
	- ▁CER
	- OU
	- IPP
	- ▁CO
	- EH
	- TE
	- WHERE
	- ASH
	- PPY
	- WAY
	- RO
	- SHE
	- OST
	- AIN
	- ▁SECOND
	- ▁PIRATE
	- ▁MINUTE
	- ABET
	- ▁DIFFEREN
	- BE
	- IGH
	- ▁COO
	- ▁WHA
	- BRUSH
	- TRA
	- ▁PRES
	- ▁TRYIN
	- ▁GIV
	- OPE
	- SHIN
	- STRO
	- SIGN
	- ▁PLU
	- ZEBRA
	- LION
	- CROCODILE
	- LATE
	- UF
	- EQUALS
	- COME
	- UBE
	- J
	- TOGETHER
	- MAYBE
	- BOX
	- CLEAN
	- THEY
	- JIBO
	- EASY
	- MOUTH
	- ▁TALK
	- ▁SKI
	- WHY
	- WICE
	- CAUSE
	- UMP
	- TRIC
	- ▁CLOS
	- ▁SEVE
	- ▁DIRT
	- ▁NUMB
	- YOU
	- PRI
	- ▁JIB
	- ETTIER
	- FFERENT
	- ERCASE
	- ROOM
	- ▁DIFF
	- ▁JELLY
	- ▁SEVENEIGHT
	- ORGE
	- ▁YELL
	- DRA
	- ▁SLOW
	- ▁MON
	- ▁BUG
	- YPE
	- ▁BRU
	- COL
	- PUS
	- WO
	- INET
	- NGRY
	- BRUSHING
	- ▁CUB
	- OCTO
	- HIC
	- UDE
	- RUB
	- MOR
	- LOCK
	- ▁BR
	- YOUR
	- ▁STR
	- ▁KNE
	- ▁CRO
	- ▁BO
	- UALLY
	- ▁TOOTHB
	- ▁ANYMO
	- UKU
	- ▁GUE
	- MA
	- ENTY
	- PHA
	- ▁QUE
	- PF
	- KE
	- NOW
	- ▁LAS
	- ▁SHIN
	- ARN
	- GE
	- ▁MAIL
	- RUSHING
	- Q
	- <sos/eos>
	init: null
	input_size: null
	ctc_conf:
	dropout_rate: 0.0
	ctc_type: builtin
	reduce: true
	ignore_nan_grad: null
	zero_infinity: true
	brctc_risk_strategy: exp
	brctc_group_strategy: end
	brctc_risk_factor: 0.0
	joint_net_conf: null
	use_preprocessor: true
	use_lang_prompt: false
	use_nlp_prompt: false
	token_type: bpe
	bpemodel: data/en_token_list/bpe_unigram1024/bpe.model
	non_linguistic_symbols: null
	cleaner: null
	g2p: null
	speech_volume_normalize: null
	rir_scp: null
	rir_apply_prob: 1.0
	noise_scp: null
	noise_apply_prob: 1.0
	noise_db_range: '13_15'
	short_noise_thres: 0.5
	aux_ctc_tasks: []
	frontend: s3prl
	frontend_conf:
	frontend_conf:
	upstream: wavlm_large
	download_dir: ./hub
	multilayer_feature: true
	fs: 16k
	specaug: specaug
	specaug_conf:
	apply_time_warp: true
	time_warp_window: 5
	time_warp_mode: bicubic
	apply_freq_mask: true
	freq_mask_width_range:
	- 0
	- 27
	num_freq_mask: 2
	apply_time_mask: true
	time_mask_width_ratio_range:
	- 0.0
	- 0.05
	num_time_mask: 5
	normalize: utterance_mvn
	normalize_conf: {}
	model: espnet
	model_conf:
	ctc_weight: 0.3
	lsm_weight: 0.1
	length_normalized_loss: false
	extract_feats_in_collect_stats: false
	preencoder: linear
	preencoder_conf:
	input_size: 1024
	output_size: 80
	encoder: transformer
	encoder_conf:
	output_size: 256
	attention_heads: 4
	linear_units: 1024
	num_blocks: 18
	dropout_rate: 0.1
	positional_dropout_rate: 0.1
	attention_dropout_rate: 0.1
	input_layer: conv2d2
	normalize_before: true
	postencoder: null
	postencoder_conf: {}
	decoder: transformer
	decoder_conf:
	attention_heads: 4
	linear_units: 2048
	num_blocks: 6
	dropout_rate: 0.1
	positional_dropout_rate: 0.1
	self_attention_dropout_rate: 0.1
	src_attention_dropout_rate: 0.1
	preprocessor: default
	preprocessor_conf: {}
	required:
	- output_dir
	- token_list
	version: '202402'
	distributed: false
	```

	</details>



	### Citing ESPnet

	```BibTex
	@inproceedings{watanabe2018espnet,
	author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
	title={{ESPnet}: End-to-End Speech Processing Toolkit},
	year={2018},
	booktitle={Proceedings of Interspeech},
	pages={2207--2211},
	doi={10.21437/Interspeech.2018-1456},
	url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
	}






	```

	or arXiv:

	```bibtex
	@misc{watanabe2018espnet,
	title={ESPnet: End-to-End Speech Processing Toolkit},
	author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
	year={2018},
	eprint={1804.00015},
	archivePrefix={arXiv},
	primaryClass={cs.CL}
	}
	```