--- tags: - espnet - audio - automatic-speech-recognition language: en datasets: - chime4 license: cc-by-4.0 --- ## ESPnet2 ASR model ### `pyf98/chime4_conformer_e12_linear1024` This model was trained by Yifan Peng 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 git checkout ad91279f0108d54bd22abe29671b376f048822c5 pip install -e . cd egs2/chime4/asr1 ./run.sh --skip_data_prep false --skip_train true --download_model pyf98/chime4_conformer_e12_linear1024 ``` # RESULTS ## Environments - date: `Wed Dec 28 15:49:24 EST 2022` - python version: `3.9.15 (main, Nov 24 2022, 14:31:59) [GCC 11.2.0]` - espnet version: `espnet 202211` - pytorch version: `pytorch 1.12.1` - Git hash: `f9a8009aef6ff9ba192a78c19b619ae4a9f3b9d2` - Commit date: `Wed Dec 28 00:30:54 2022 -0500` ## asr_train_asr_conformer_e12_linear1024_raw_en_char_sp ### WER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/dt05_real_beamformit_5mics|1640|27119|92.8|5.8|1.5|0.6|7.8|56.5| |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/dt05_simu_beamformit_5mics|1640|27120|91.3|6.7|2.0|0.8|9.5|60.5| |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/et05_real_beamformit_5mics|1320|21409|88.6|9.2|2.1|1.2|12.5|63.8| |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/et05_simu_beamformit_5mics|1320|21416|86.5|10.4|3.1|1.3|14.8|70.9| ### CER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/dt05_real_beamformit_5mics|1640|160390|96.9|1.6|1.5|0.7|3.8|56.5| |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/dt05_simu_beamformit_5mics|1640|160400|96.0|2.0|2.0|1.0|4.9|60.5| |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/et05_real_beamformit_5mics|1320|126796|94.8|2.8|2.3|1.2|6.4|63.9| |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/et05_simu_beamformit_5mics|1320|126812|93.1|3.4|3.4|1.5|8.4|70.9| ### TER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| ## ASR config
expand ``` config: conf/tuning/train_asr_conformer_e12_linear1024.yaml print_config: false log_level: INFO dry_run: false iterator_type: sequence output_dir: exp/asr_train_asr_conformer_e12_linear1024_raw_en_char_sp ngpu: 1 seed: 2022 num_workers: 4 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: false sharded_ddp: false cudnn_enabled: true cudnn_benchmark: false cudnn_deterministic: true collect_stats: false write_collected_feats: false max_epoch: 60 patience: null val_scheduler_criterion: - valid - loss early_stopping_criterion: - valid - loss - min best_model_criterion: - - valid - acc - max keep_nbest_models: 10 nbest_averaging_interval: 0 grad_clip: 5.0 grad_clip_type: 2.0 grad_noise: false accum_grad: 1 no_forward_run: false resume: true train_dtype: float32 use_amp: true 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: [] ignore_init_mismatch: false freeze_param: [] num_iters_per_epoch: null batch_size: 20 valid_batch_size: null batch_bins: 15000000 valid_batch_bins: null train_shape_file: - exp/asr_stats_raw_en_char_sp/train/speech_shape - exp/asr_stats_raw_en_char_sp/train/text_shape.char valid_shape_file: - exp/asr_stats_raw_en_char_sp/valid/speech_shape - exp/asr_stats_raw_en_char_sp/valid/text_shape.char batch_type: numel valid_batch_type: null fold_length: - 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_noisy_si284_sp/wav.scp - speech - kaldi_ark - - dump/raw/tr05_multi_noisy_si284_sp/text - text - text valid_data_path_and_name_and_type: - - dump/raw/dt05_multi_isolated_1ch_track/wav.scp - speech - kaldi_ark - - dump/raw/dt05_multi_isolated_1ch_track/text - text - text allow_variable_data_keys: false max_cache_size: 0.0 max_cache_fd: 32 valid_max_cache_size: null optim: adam optim_conf: lr: 0.001 weight_decay: 1.0e-06 scheduler: warmuplr scheduler_conf: warmup_steps: 25000 token_list: - - - - E - T - A - N - I - O - S - R - H - L - D - C - U - M - P - F - G - Y - W - B - V - K - . - X - '''' - J - Q - Z - ',' - '-' - '"' - - '*' - ':' - ( - ) - '?' - '&' - ; - '!' - / - '{' - '}' - '1' - '2' - '0' - $ - '8' - '9' - '6' - '3' - '5' - '7' - '4' - '~' - '`' - _ - <*IN*> - <*MR.*> - \ - ^ - init: null input_size: null ctc_conf: dropout_rate: 0.0 ctc_type: builtin reduce: true ignore_nan_grad: null zero_infinity: true joint_net_conf: null use_preprocessor: true token_type: char bpemodel: null non_linguistic_symbols: data/nlsyms.txt 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 frontend: default frontend_conf: n_fft: 512 win_length: 400 hop_length: 160 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: 2 normalize: global_mvn normalize_conf: stats_file: exp/asr_stats_raw_en_char_sp/train/feats_stats.npz model: espnet model_conf: ctc_weight: 0.3 lsm_weight: 0.1 length_normalized_loss: false preencoder: null preencoder_conf: {} encoder: conformer encoder_conf: output_size: 256 attention_heads: 4 linear_units: 1024 num_blocks: 12 dropout_rate: 0.1 positional_dropout_rate: 0.1 attention_dropout_rate: 0.1 input_layer: conv2d normalize_before: true macaron_style: true rel_pos_type: latest pos_enc_layer_type: rel_pos selfattention_layer_type: rel_selfattn activation_type: swish use_cnn_module: true cnn_module_kernel: 31 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: '202211' 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} } ```