ESPnet2 pretrained model, Pavel Denisov/swahili_asr_train_asr_conformer_raw_sw_bpe100_sp_valid.acc.ave, fs=16k, lang=sw
Creators: name: Denisov, Pavel
Publisher: name: Zenodo
Year: 2021
Subjects: ESPnet
deep-learning
python
pytorch
speech-recognition
speech-synthesis
speech-translation
machine-translation

description: This model was trained by Pavel Denisov using swahili recipe in espnet. <strong>Python API</strong> <pre><code class="language-python">See https://github.com/espnet/espnet_model_zoo</code></pre> <strong>Evaluate in the recipe</strong> <pre><code class="language-bash">git clone https://github.com/espnet/espnet cd espnet git checkout 401c39106b0e0dec2a9a40876a5057c3cad701e7 pip install -e . cd egs2/swahili/asr1 ./run.sh --skip_data_prep false --skip_train true --download_model Pavel Denisov/swahili_asr_train_asr_conformer_raw_sw_bpe100_sp_valid.acc.ave</code> </pre> <strong>Results</strong> <pre><code> # RESULTS ## Environments - date: `Fri Aug 20 10:22:09 CEST 2021` - python version: `3.9.6 (default, Jul 16 2021, 00:00:00) [GCC 11.1.1 20210531 (Red Hat 11.1.1-3)]` - espnet version: `espnet 0.10.2a1` - pytorch version: `pytorch 1.9.0+cu111` - Git hash: `401c39106b0e0dec2a9a40876a5057c3cad701e7` - Commit date: `Wed Aug 18 14:25:46 2021 -0400` ## asr_train_asr_conformer_raw_sw_bpe100_sp ### WER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_lm_lm_train_lm_transformer_sw_bpe100_valid.loss.ave_asr_model_valid.acc.ave/test_iwslt_swa|868|18332|92.8|6.6|0.7|5.4|12.6|68.2| |decode_asr_lm_lm_train_lm_transformer_sw_bpe100_valid.loss.ave_asr_model_valid.acc.ave/test_iwslt_swa_raw|868|18412|82.0|17.3|0.7|5.0|22.9|94.6| |decode_asr_lm_lm_train_lm_transformer_sw_bpe100_valid.loss.ave_asr_model_valid.acc.ave/test_iwslt_swc|868|19504|84.5|12.7|2.8|2.5|18.0|84.2| |decode_asr_lm_lm_train_lm_transformer_sw_bpe100_valid.loss.ave_asr_model_valid.acc.ave/test_iwslt_swc_raw|868|19512|76.2|21.4|2.5|2.1|26.0|96.1| ### CER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_lm_lm_train_lm_transformer_sw_bpe100_valid.loss.ave_asr_model_valid.acc.ave/test_iwslt_swa|868|117682|98.2|1.1|0.7|4.6|6.4|68.3| |decode_asr_lm_lm_train_lm_transformer_sw_bpe100_valid.loss.ave_asr_model_valid.acc.ave/test_iwslt_swa_raw|868|119860|95.7|2.0|2.3|4.2|8.5|94.7| |decode_asr_lm_lm_train_lm_transformer_sw_bpe100_valid.loss.ave_asr_model_valid.acc.ave/test_iwslt_swc|868|119172|96.1|1.7|2.3|2.2|6.2|84.2| |decode_asr_lm_lm_train_lm_transformer_sw_bpe100_valid.loss.ave_asr_model_valid.acc.ave/test_iwslt_swc_raw|868|121352|94.1|2.1|3.8|2.0|7.9|96.1| ### TER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_lm_lm_train_lm_transformer_sw_bpe100_valid.loss.ave_asr_model_valid.acc.ave/test_iwslt_swa|868|74220|96.2|2.6|1.1|4.0|7.7|68.3| |decode_asr_lm_lm_train_lm_transformer_sw_bpe100_valid.loss.ave_asr_model_valid.acc.ave/test_iwslt_swa_raw|868|76488|90.7|4.0|5.3|5.1|14.4|94.9| |decode_asr_lm_lm_train_lm_transformer_sw_bpe100_valid.loss.ave_asr_model_valid.acc.ave/test_iwslt_swc|868|74644|93.2|4.0|2.8|2.3|9.1|84.2| |decode_asr_lm_lm_train_lm_transformer_sw_bpe100_valid.loss.ave_asr_model_valid.acc.ave/test_iwslt_swc_raw|868|77530|87.9|5.2|6.9|2.6|14.8|96.7|</code></pre> <strong>ASR config</strong> <pre><code>config: conf/train_asr_likels_ctc5_initru_freeze01.yaml print_config: false log_level: INFO dry_run: false iterator_type: sequence output_dir: exp/asr_train_asr_likels_ctc5_initru_freeze01_raw_sw_bpe100_sp/ ngpu: 0 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: null 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: 35 patience: null val_scheduler_criterion: - valid - loss early_stopping_criterion: - valid - loss - min best_model_criterion: - - valid - acc - max keep_nbest_models: - 1 grad_clip: 5.0 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_tensorboard: true use_wandb: false wandb_project: null wandb_id: null detect_anomaly: false pretrain_path: null init_param: - models/ru_open_stt_conformer.pth:::decoder.embed.0,decoder.output_layer,ctc.ctc_lo,encoder.embed freeze_param: - encoder.encoders.0 num_iters_per_epoch: null batch_size: 20 valid_batch_size: null batch_bins: 20000000 valid_batch_bins: null train_shape_file: - exp/asr_stats_raw_sw_bpe100_sp/train/speech_shape - exp/asr_stats_raw_sw_bpe100_sp/train/text_shape.bpe valid_shape_file: - exp/asr_stats_raw_sw_bpe100_sp/valid/speech_shape - exp/asr_stats_raw_sw_bpe100_sp/valid/text_shape.bpe 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/train_babel_alffa_gamayun_iwslt_sp/wav.scp - speech - sound - - dump/raw/train_babel_alffa_gamayun_iwslt_sp/text - text - text valid_data_path_and_name_and_type: - - dump/raw/valid_alffa_iwslt/wav.scp - speech - sound - - dump/raw/valid_alffa_iwslt/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: 0.005 scheduler: warmuplr scheduler_conf: warmup_steps: 10000 token_list: - - - - - - - - - - - - - - - - - - - ▁ - a - o - n - e - u - i - na - li - ka - ta - h - s - wa - ▁wa - ▁ku - m - ni - ▁m - ▁na - ▁ya - sa - ma - r - ▁u - ki - ku - ▁ha - hi - g - ri - ▁ni - za - y - we - zi - si - d - la - f - tu - c - ti - ▁ma - ▁kwa - b - le - yo - hu - mi - bi - me - di - z - ko - ▁i - l - ba - fu - v - ▁si - pa - ra - mu - kuwa - ji - ke - ja - mba - ▁ehhe - to - t - ye - ▁ki - k - j - w - p - x - '''' - q - init: null input_size: null ctc_conf: ignore_nan_grad: true model_conf: ctc_weight: 0.5 lsm_weight: 0.1 length_normalized_loss: false use_preprocessor: true token_type: bpe bpemodel: data/sw_token_list/bpe_unigram100/bpe.model non_linguistic_symbols: local/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' frontend: default frontend_conf: n_fft: 512 hop_length: 256 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 - 30 num_freq_mask: 2 apply_time_mask: true time_mask_width_range: - 0 - 40 num_time_mask: 2 normalize: global_mvn normalize_conf: stats_file: exp/asr_stats_raw_sw_bpe100_sp/train/feats_stats.npz preencoder: null preencoder_conf: {} encoder: conformer encoder_conf: output_size: 512 attention_heads: 8 linear_units: 2048 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 pos_enc_layer_type: rel_pos selfattention_layer_type: rel_selfattn activation_type: swish use_cnn_module: true cnn_module_kernel: 31 decoder: transformer decoder_conf: attention_heads: 8 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 required: - output_dir - token_list version: 0.9.8 distributed: false</code></pre> <strong>LM config</strong> <pre><code>config: conf/train_lm_transformer.yaml print_config: false log_level: INFO dry_run: false iterator_type: sequence output_dir: exp/lm_train_lm_transformer_sw_bpe100 ngpu: 1 seed: 0 num_workers: 1 num_att_plot: 3 dist_backend: nccl dist_init_method: env:// dist_world_size: 3 dist_rank: 0 local_rank: 0 dist_master_addr: localhost dist_master_port: 50355 dist_launcher: null multiprocessing_distributed: true unused_parameters: false sharded_ddp: false cudnn_enabled: true cudnn_benchmark: false cudnn_deterministic: true collect_stats: false write_collected_feats: false max_epoch: 30 patience: null val_scheduler_criterion: - valid - loss early_stopping_criterion: - valid - loss - min best_model_criterion: - - valid - loss - min 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 use_tensorboard: true use_wandb: false wandb_project: null wandb_id: null detect_anomaly: false pretrain_path: null init_param: [] freeze_param: [] num_iters_per_epoch: null batch_size: 20 valid_batch_size: null batch_bins: 5000000 valid_batch_bins: null train_shape_file: - exp/lm_stats_sw_bpe100/train/text_shape.bpe valid_shape_file: - exp/lm_stats_sw_bpe100/valid/text_shape.bpe batch_type: numel 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/lm_train.txt - text - text valid_data_path_and_name_and_type: - - dump/raw/valid_alffa_iwslt/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 scheduler: warmuplr scheduler_conf: warmup_steps: 25000 token_list: - - - - - - - - - - - - - - - - - - - ▁ - a - o - n - e - u - i - na - li - ka - ta - h - s - wa - ▁wa - ▁ku - m - ni - ▁m - ▁na - ▁ya - sa - ma - r - ▁u - ki - ku - ▁ha - hi - g - ri - ▁ni - za - y - we - zi - si - d - la - f - tu - c - ti - ▁ma - ▁kwa - b - le - yo - hu - mi - bi - me - di - z - ko - ▁i - l - ba - fu - v - ▁si - pa - ra - mu - kuwa - ji - ke - ja - mba - ▁ehhe - to - t - ye - ▁ki - k - j - w - p - x - '''' - q - init: null model_conf: ignore_id: 0 use_preprocessor: true token_type: bpe bpemodel: data/sw_token_list/bpe_unigram100/bpe.model non_linguistic_symbols: local/nlsyms.txt cleaner: null g2p: null lm: transformer lm_conf: pos_enc: null embed_unit: 128 att_unit: 512 head: 8 unit: 2048 layer: 16 dropout_rate: 0.1 required: - output_dir - token_list version: 0.9.8 distributed: true</code></pre>