This model was trained by coppersj using yesno recipe in espnet. Python API See https://github.com/espnet/espnet_model_zoo Evaluate in the recipe git clone https://github.com/espnet/espnet cd espnet pip install -e . cd egs2/yesno/asr1 ./run.sh --skip_data_prep false --skip_train true --download_model coppersj/yesno_asr_train_asr_raw_char_valid.acc.ave Results # RESULTS ## Environments - date: `Mon Sep 21 06:02:39 UTC 2020` - python version: `3.6.9 (default, Jul 17 2020, 12:50:27) [GCC 8.4.0]` - espnet version: `espnet 0.9.3` - pytorch version: `pytorch 1.6.0+cu101` - Git hash: `624fdc847222b48dd0d34aef44f9e0cbec05756b` - Commit date: `Sun Sep 20 14:22:37 2020 +0000` ## asr_train_asr_raw_char ### WER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_model_valid.acc.ave/test_yesno|30|240|39.6|60.4|0.0|371.7|432.1|100.0| |decode_asr_model_valid.acc.ave/train_dev|2|16|62.5|37.5|0.0|375.0|412.5|100.0| ### CER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_model_valid.acc.ave/test_yesno|30|835|47.9|52.1|0.0|303.0|355.1|100.0| |decode_asr_model_valid.acc.ave/train_dev|2|52|65.4|34.6|0.0|334.6|369.2|100.0| ASR config config: conf/train_asr.yaml print_config: false log_level: INFO dry_run: false iterator_type: sequence output_dir: exp/asr_train_asr_raw_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 cudnn_enabled: true cudnn_benchmark: false cudnn_deterministic: true collect_stats: false write_collected_feats: false max_epoch: 20 patience: 3 val_scheduler_criterion: - valid - acc early_stopping_criterion: - valid - acc - max best_model_criterion: - - valid - acc - max keep_nbest_models: 1 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: false log_interval: null pretrain_path: [] pretrain_key: [] num_iters_per_epoch: null batch_size: 5 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.char valid_shape_file: - exp/asr_stats_raw/valid/speech_shape - exp/asr_stats_raw/valid/text_shape.char 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: lr: 1.0 rho: 0.95 eps: 1.0e-08 weight_decay: 0 scheduler: null scheduler_conf: {} token_list: - - - - N - O - Y - E - S - init: chainer input_size: null ctc_conf: dropout_rate: 0.0 ctc_type: builtin reduce: true model_conf: ctc_weight: 0.5 use_preprocessor: true token_type: char bpemodel: null 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: rnn_type: lstm bidirectional: true use_projection: true num_layers: 3 hidden_size: 128 output_size: 128 decoder: rnn decoder_conf: rnn_type: lstm num_layers: 1 hidden_size: 128 sampling_probability: 0.0 att_conf: atype: location adim: 128 aconv_chans: 10 aconv_filts: 100 required: - output_dir - token_list distributed: false LM config NONE