--- tags: - espnet - audio - speech-enhancement-recognition language: en datasets: - chime4 license: cc-by-4.0 --- ## ESPnet2 EnhS2T model ### `Yoshiki/chime4_enh_asr1_wpd_wavlm_conformer` This model was trained by Yoshiki using chime4 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 8ed83f45d5aa2ca6b3635e44b9c29afb9b5fb600 pip install -e . cd egs2/chime4/enh_asr1 ./run.sh --skip_data_prep false --skip_train true --download_model Yoshiki/chime4_enh_asr1_wpd_wavlm_conformer ``` # RESULTS ## Environments - date: `Tue Oct 11 02:40:53 UTC 2022` - python version: `3.7.4 (default, Aug 13 2019, 20:35:49) [GCC 7.3.0]` - espnet version: `espnet 202207` - pytorch version: `pytorch 1.10.1+cu111` - Git hash: `` - Commit date: `` ## enh_asr_train_enh_asr_wpd_init_noenhloss_wavlm_conformer_raw_en_char ### WER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_transformer_largelm_normalize_output_wavtrue_lm_lm_train_lm_transformer_en_char_valid.loss.ave_enh_asr_model_valid.acc.ave_10best/dt05_real_isolated_6ch_track|1640|27119|98.8|0.9|0.2|0.2|1.3|16.2| |decode_asr_transformer_largelm_normalize_output_wavtrue_lm_lm_train_lm_transformer_en_char_valid.loss.ave_enh_asr_model_valid.acc.ave_10best/dt05_simu_isolated_6ch_track|1640|27120|98.9|0.9|0.2|0.1|1.3|15.2| |decode_asr_transformer_largelm_normalize_output_wavtrue_lm_lm_train_lm_transformer_en_char_valid.loss.ave_enh_asr_model_valid.acc.ave_10best/et05_real_isolated_6ch_track|1320|21409|98.4|1.4|0.2|0.2|1.8|20.6| |decode_asr_transformer_largelm_normalize_output_wavtrue_lm_lm_train_lm_transformer_en_char_valid.loss.ave_enh_asr_model_valid.acc.ave_10best/et05_simu_isolated_6ch_track|1320|21416|98.9|1.0|0.2|0.1|1.2|15.2| ### CER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_transformer_largelm_normalize_output_wavtrue_lm_lm_train_lm_transformer_en_char_valid.loss.ave_enh_asr_model_valid.acc.ave_10best/dt05_real_isolated_6ch_track|1640|160390|99.7|0.1|0.2|0.2|0.5|16.2| |decode_asr_transformer_largelm_normalize_output_wavtrue_lm_lm_train_lm_transformer_en_char_valid.loss.ave_enh_asr_model_valid.acc.ave_10best/dt05_simu_isolated_6ch_track|1640|160400|99.7|0.1|0.2|0.1|0.5|15.2| |decode_asr_transformer_largelm_normalize_output_wavtrue_lm_lm_train_lm_transformer_en_char_valid.loss.ave_enh_asr_model_valid.acc.ave_10best/et05_real_isolated_6ch_track|1320|126796|99.5|0.2|0.3|0.2|0.7|20.6| |decode_asr_transformer_largelm_normalize_output_wavtrue_lm_lm_train_lm_transformer_en_char_valid.loss.ave_enh_asr_model_valid.acc.ave_10best/et05_simu_isolated_6ch_track|1320|126812|99.7|0.2|0.2|0.1|0.5|15.2| ### TER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| ## EnhS2T config
expand ``` config: conf/tuning/train_enh_asr_wpd_init_noenhloss_wavlm_conformer.yaml print_config: false log_level: INFO dry_run: false iterator_type: sequence output_dir: exp/enh_asr_train_enh_asr_wpd_init_noenhloss_wavlm_conformer_raw_en_char ngpu: 1 seed: 0 num_workers: 1 num_att_plot: 3 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: true sharded_ddp: false cudnn_enabled: true cudnn_benchmark: false cudnn_deterministic: true collect_stats: false write_collected_feats: false max_epoch: 31 patience: 10 val_scheduler_criterion: - valid - loss early_stopping_criterion: - valid - loss - min best_model_criterion: - - valid - acc - max - - train - loss - min keep_nbest_models: 10 nbest_averaging_interval: 0 grad_clip: 1 grad_clip_type: 2.0 grad_noise: false accum_grad: 2 no_forward_run: false resume: true train_dtype: float32 use_amp: false log_interval: null 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 pretrain_path: null init_param: - ../enh1/exp/enh_train_enh_beamformer_wpd_ci_sdr_shorttap_raw/valid.loss.best.pth:separator:enh_model.separator - ../asr1/exp/asr_train_asr_conformer_wavlm2_raw_en_char/valid.acc.best.pth:frontend:s2t_model.frontend - ../asr1/exp/asr_train_asr_conformer_wavlm2_raw_en_char/valid.acc.best.pth:preencoder:s2t_model.preencoder - ../asr1/exp/asr_train_asr_conformer_wavlm2_raw_en_char/valid.acc.best.pth:encoder:s2t_model.encoder - ../asr1/exp/asr_train_asr_conformer_wavlm2_raw_en_char/valid.acc.best.pth:ctc:s2t_model.ctc - ../asr1/exp/asr_train_asr_conformer_wavlm2_raw_en_char/valid.acc.best.pth:decoder:s2t_model.decoder ignore_init_mismatch: false freeze_param: - s2t_model.frontend.upstream num_iters_per_epoch: null batch_size: 16 valid_batch_size: null batch_bins: 1000000 valid_batch_bins: null train_shape_file: - exp/enh_asr_stats_raw_en_char/train/speech_shape - exp/enh_asr_stats_raw_en_char/train/speech_ref1_shape - exp/enh_asr_stats_raw_en_char/train/text_spk1_shape.char valid_shape_file: - exp/enh_asr_stats_raw_en_char/valid/speech_shape - exp/enh_asr_stats_raw_en_char/valid/speech_ref1_shape - exp/enh_asr_stats_raw_en_char/valid/text_spk1_shape.char batch_type: folded valid_batch_type: null fold_length: - 80000 - 80000 - 150 sort_in_batch: descending sort_batch: descending multiple_iterator: false chunk_length: 500 chunk_shift_ratio: 0.5 num_cache_chunks: 1024 train_data_path_and_name_and_type: - - dump/raw/tr05_multi_isolated_6ch_track/wav.scp - speech - sound - - dump/raw/tr05_multi_isolated_6ch_track/spk1.scp - speech_ref1 - sound - - dump/raw/tr05_multi_isolated_6ch_track/text_spk1 - text_spk1 - text valid_data_path_and_name_and_type: - - dump/raw/dt05_multi_isolated_6ch_track/wav.scp - speech - sound - - dump/raw/dt05_multi_isolated_6ch_track/spk1.scp - speech_ref1 - sound - - dump/raw/dt05_multi_isolated_6ch_track/text_spk1 - text_spk1 - text allow_variable_data_keys: false max_cache_size: 0.0 max_cache_fd: 32 valid_max_cache_size: null optim: sgd optim_conf: lr: 0.001 momentum: 0.9 scheduler: null scheduler_conf: {} token_list: data/en_token_list/char/tokens.txt src_token_list: null init: xavier_uniform input_size: null ctc_conf: dropout_rate: 0.0 ctc_type: builtin reduce: true ignore_nan_grad: null zero_infinity: true enh_criterions: - name: ci_sdr conf: filter_length: 512 wrapper: fixed_order wrapper_conf: weight: 0.1 diar_num_spk: null diar_input_size: null enh_model_conf: stft_consistency: false loss_type: mask_mse mask_type: null asr_model_conf: ctc_weight: 0.3 lsm_weight: 0.1 length_normalized_loss: false extract_feats_in_collect_stats: false st_model_conf: stft_consistency: false loss_type: mask_mse mask_type: null diar_model_conf: diar_weight: 1.0 attractor_weight: 1.0 subtask_series: - enh - asr model_conf: calc_enh_loss: false bypass_enh_prob: 0.0 use_preprocessor: true token_type: char bpemodel: null src_token_type: bpe src_bpemodel: null non_linguistic_symbols: data/nlsyms.txt cleaner: null g2p: null text_name: - text_spk1 enh_encoder: stft enh_encoder_conf: n_fft: 512 win_length: 400 hop_length: 128 use_builtin_complex: false enh_separator: wpe_beamformer enh_separator_conf: num_spk: 1 loss_type: spectrum use_wpe: false wnet_type: blstmp wlayers: 3 wunits: 512 wprojs: 512 wdropout_rate: 0.0 taps: 3 delay: 3 use_dnn_mask_for_wpe: true use_beamformer: true bnet_type: blstmp blayers: 3 bunits: 512 bprojs: 512 badim: 320 ref_channel: 4 use_noise_mask: true beamformer_type: wpd_souden bdropout_rate: 0.0 enh_decoder: stft enh_decoder_conf: n_fft: 512 win_length: 400 hop_length: 128 enh_mask_module: multi_mask enh_mask_module_conf: {} 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 - 100 num_freq_mask: 4 apply_time_mask: true time_mask_width_range: - 0 - 40 num_time_mask: 2 normalize: utterance_mvn normalize_conf: {} asr_preencoder: linear asr_preencoder_conf: input_size: 1024 output_size: 80 asr_encoder: conformer asr_encoder_conf: output_size: 256 attention_heads: 4 linear_units: 2048 num_blocks: 12 dropout_rate: 0.1 positional_dropout_rate: 0.1 attention_dropout_rate: 0.0 input_layer: conv2d2 normalize_before: true macaron_style: true pos_enc_layer_type: rel_pos selfattention_layer_type: rel_selfattn activation_type: swish use_cnn_module: true cnn_module_kernel: 15 asr_postencoder: null asr_postencoder_conf: {} asr_decoder: transformer asr_decoder_conf: input_layer: embed attention_heads: 4 linear_units: 2048 num_blocks: 6 dropout_rate: 0.1 positional_dropout_rate: 0.1 self_attention_dropout_rate: 0.0 src_attention_dropout_rate: 0.0 st_preencoder: null st_preencoder_conf: {} st_encoder: rnn st_encoder_conf: {} st_postencoder: null st_postencoder_conf: {} st_decoder: rnn st_decoder_conf: {} st_extra_asr_decoder: rnn st_extra_asr_decoder_conf: {} st_extra_mt_decoder: rnn st_extra_mt_decoder_conf: {} diar_frontend: default diar_frontend_conf: {} diar_specaug: null diar_specaug_conf: {} diar_normalize: utterance_mvn diar_normalize_conf: {} diar_encoder: transformer diar_encoder_conf: {} diar_decoder: linear diar_decoder_conf: {} label_aggregator: label_aggregator label_aggregator_conf: {} diar_attractor: null diar_attractor_conf: {} required: - output_dir version: '202207' distributed: false ```
### 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} } ```