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ESPnet2 pretrained model, kamo-naoyuki/mini_an4_asr_train_raw_bpe_valid.acc.best, fs=16k, lang=en

Authors: kamo-naoyuki;

ESPnet2 pretrained model, kamo-naoyuki/mini_an4_asr_train_raw_bpe_valid.acc.best, fs=16k, lang=en

Abstract

This model was trained by kamo-naoyuki using mini_an4 recipe in espnet. Python APISee https://github.com/espnet/espnet_model_zoo Evaluate in the recipegit clone https://github.com/espnet/espnet cd espnet git checkout 04c66e2796213f4610e03c07ec594ee64878e893 pip install -e . cd egs2/mini_an4/asr1 ./run.sh --skip_data_prep false --skip_train true --download_model kamo-naoyuki/mini_an4_asr_train_raw_bpe_valid.acc.best Results # RESULTS ## Environments - date: `Thu Jul 23 03:18:58 JST 2020` - python version: `3.7.3 (default, Mar 27 2019, 22:11:17) [GCC 7.3.0]` - espnet version: `espnet 0.8.0` - pytorch version: `pytorch 1.0.1` - Git hash: `31794e2aec89e6159c1ac32643d4c09989200a30` - Commit date: `Thu Jul 23 03:17:45 2020 +0900` ## asr_train_raw_bpe ### WER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_test_decode_lm_train_bpe_valid.loss.best_asr_model_valid.acc.best|2|10|0.0|20.0|80.0|0.0|100.0|100.0| |decode_test_seg_decode_lm_train_bpe_valid.loss.best_asr_model_valid.acc.best|2|10|0.0|20.0|80.0|0.0|100.0|100.0| |decode_train_dev_decode_lm_train_bpe_valid.loss.best_asr_model_valid.acc.best|1|1|0.0|100.0|0.0|0.0|100.0|100.0| ### CER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_test_decode_lm_train_bpe_valid.loss.best_asr_model_valid.acc.best|2|67|53.7|44.8|1.5|206.0|252.2|100.0| |decode_test_seg_decode_lm_train_bpe_valid.loss.best_asr_model_valid.acc.best|2|67|53.7|44.8|1.5|206.0|252.2|100.0| |decode_train_dev_decode_lm_train_bpe_valid.loss.best_asr_model_valid.acc.best|1|3|33.3|66.7|0.0|1200.0|1266.7|100.0| ### TER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_test_decode_lm_train_bpe_valid.loss.best_asr_model_valid.acc.best|2|45|15.6|82.2|2.2|208.9|293.3|100.0| |decode_test_seg_decode_lm_train_bpe_valid.loss.best_asr_model_valid.acc.best|2|45|15.6|82.2|2.2|208.9|293.3|100.0| |decode_train_dev_decode_lm_train_bpe_valid.loss.best_asr_model_valid.acc.best|1|4|25.0|75.0|0.0|550.0|625.0|100.0| ASR configconfig: null print_config: false log_level: INFO dry_run: false iterator_type: sequence output_dir: exp/asr_train_raw_bpe 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 cudnn_enabled: true cudnn_benchmark: false cudnn_deterministic: true collect_stats: false write_collected_feats: false max_epoch: 40 patience: null val_scheduler_criterion: - valid - loss early_stopping_criterion: - valid - loss - min best_model_criterion: - - train - loss - min - - valid - loss - min - - train - acc - max - - valid - acc - max keep_nbest_models: 10 grad_clip: 5.0 grad_noise: false accum_grad: 1 no_forward_run: false resume: true train_dtype: float32 log_interval: null pretrain_path: [] pretrain_key: [] num_iters_per_epoch: null batch_size: 20 valid_batch_size: null batch_bins: 1000000 valid_batch_bins: null train_shape_file: - exp/asr_stats_raw/train/speech_shape - exp/asr_stats_raw/train/text_shape.bpe valid_shape_file: - exp/asr_stats_raw/valid/speech_shape - exp/asr_stats_raw/valid/text_shape.bpe batch_type: folded 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/train_nodev/wav.scp - speech - sound - - dump/raw/train_nodev/text - text - text valid_data_path_and_name_and_type: - - dump/raw/train_dev/wav.scp - speech - sound - - dump/raw/train_dev/text - text - text allow_variable_data_keys: false max_cache_size: 0.0 valid_max_cache_size: null optim: adadelta optim_conf: {} scheduler: null scheduler_conf: {} token_list: - - - T - "\u2581" - I - H - G - O - AR - "\u2581T" - NE - E - EN - Y - "\u2581E" - "\u2581S" - EVEN - F - M - C - R - D - N - W - ENT - L - init: null input_size: null ctc_conf: dropout_rate: 0.0 ctc_type: builtin reduce: true model_conf: ctc_weight: 0.5 ignore_id: -1 lsm_weight: 0.0 length_normalized_loss: false report_cer: true report_wer: true sym_space: sym_blank: use_preprocessor: true token_type: bpe bpemodel: data/token_list/bpe_unigram30/bpe.model non_linguistic_symbols: null cleaner: null g2p: null frontend: default frontend_conf: fs: 16k specaug: null specaug_conf: {} normalize: global_mvn normalize_conf: stats_file: exp/asr_stats_raw/train/feats_stats.npz encoder: rnn encoder_conf: {} decoder: rnn decoder_conf: {} required: - output_dir - token_list distributed: false LM configconfig: null print_config: false log_level: INFO dry_run: false iterator_type: sequence output_dir: exp/lm_train_bpe 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 cudnn_enabled: true cudnn_benchmark: false cudnn_deterministic: true collect_stats: false write_collected_feats: false max_epoch: 40 patience: null val_scheduler_criterion: - valid - loss early_stopping_criterion: - valid - loss - min best_model_criterion: - - train - loss - min - - valid - loss - min - - train - acc - max - - valid - acc - max keep_nbest_models: 10 grad_clip: 5.0 grad_noise: false accum_grad: 1 no_forward_run: false resume: true train_dtype: float32 log_interval: null pretrain_path: [] pretrain_key: [] num_iters_per_epoch: null batch_size: 20 valid_batch_size: null batch_bins: 1000000 valid_batch_bins: null train_shape_file: - exp/lm_stats/train/text_shape.bpe valid_shape_file: - exp/lm_stats/valid/text_shape.bpe batch_type: folded valid_batch_type: null fold_length: - 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/srctexts - text - text valid_data_path_and_name_and_type: - - dump/raw/train_dev/text - text - text allow_variable_data_keys: false max_cache_size: 0.0 valid_max_cache_size: null optim: adadelta optim_conf: {} scheduler: null scheduler_conf: {} token_list: - - - T - "\u2581" - I - H - G - O - AR - "\u2581T" - NE - E - EN - Y - "\u2581E" - "\u2581S" - EVEN - F - M - C - R - D - N - W - ENT - L - init: null model_conf: ignore_id: 0 use_preprocessor: true token_type: bpe bpemodel: data/token_list/bpe_unigram30/bpe.model non_linguistic_symbols: null cleaner: null g2p: null lm: seq_rnn lm_conf: {} required: - output_dir - token_list distributed: false

Keywords

python, speech-synthesis, pytorch, machine-translation, ESPnet, speech-translation, deep-learning, speech-recognition

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