ESPnet2 pretrained model, kan-bayashi/csmsc_tts_train_tacotron2_raw_phn_pypinyin_g2p_phone_train.loss.best, fs=24000, lang=zh
Creators: name: Kan-Bayashi
Publisher: name: Zenodo
Year: 2020
Subjects: ESPnet
deep-learning
python
pytorch
speech-recognition
speech-synthesis
speech-translation
machine-translation

description: This model was trained by kan-bayashi using csmsc/tts1 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 47f51a77906c4c44d0da23da04e68676e4b931ab pip install -e . cd egs2/csmsc/tts1 # Download the model file here ./run.sh --skip_data_prep false --skip_train true --download_model kan-bayashi/csmsc_tts_train_tacotron2_raw_phn_pypinyin_g2p_phone_train.loss.best</code> </pre> <strong>Config</strong> <pre><code>config: conf/train.yaml print_config: false log_level: INFO dry_run: false iterator_type: sequence output_dir: exp/tts_train_raw_phn_pypinyin_g2p_phone 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: 200 patience: null val_scheduler_criterion: - valid - loss early_stopping_criterion: - valid - loss - min best_model_criterion: - - valid - loss - min - - train - loss - min keep_nbest_models: 5 grad_clip: 1.0 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: 3750000 valid_batch_bins: null train_shape_file: - exp/tts_stats_raw_phn_pypinyin_g2p_phone/train/text_shape.phn - exp/tts_stats_raw_phn_pypinyin_g2p_phone/train/speech_shape valid_shape_file: - exp/tts_stats_raw_phn_pypinyin_g2p_phone/valid/text_shape.phn - exp/tts_stats_raw_phn_pypinyin_g2p_phone/valid/speech_shape batch_type: numel valid_batch_type: null fold_length: - 150 - 240000 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/tr_no_dev/text - text - text - - dump/raw/tr_no_dev/wav.scp - speech - sound valid_data_path_and_name_and_type: - - dump/raw/dev/text - text - text - - dump/raw/dev/wav.scp - speech - sound allow_variable_data_keys: false max_cache_size: 0.0 valid_max_cache_size: null optim: adam optim_conf: lr: 0.001 eps: 1.0e-06 weight_decay: 0.0 scheduler: null scheduler_conf: {} token_list: - - - "\uFF30" - "\uFF22" - "\xFC" - an - ueng3 - '2' - uen - ei - ua - ao - u - ueng4 - uo - ang - ou - v2 - ueng1 - o - io1 - "\xFCn3" - er - ve4 - o3 - uai2 - uen3 - uen1 - uai3 - "\xFCe3" - iou1 - iong2 - ia2 - uai1 - iong1 - "\xFCan1" - "\xFCe1" - v4 - ua3 - ia - iong3 - uei3 - ua2 - ia3 - uei1 - o1 - o4 - "\xFCn2" - un2 - er3 - "\xFCn1" - uen4 - un3 - iu1 - "\xFCn4" - uen2 - "\xFCan3" - un4 - "\xFCan4" - iu3 - ua1 - uei2 - "\uFF01" - iou4 - iou2 - er4 - o2 - ei1 - iao2 - uang4 - "\xFC1" - ui2 - v3 - uang2 - iong4 - un1 - ui1 - ua4 - ao2 - en - a - iu2 - uang1 - uang3 - "\xFCe2" - in3 - "\uFF1F" - uai4 - "\xFCe4" - uan2 - ou2 - eng3 - ui3 - uan4 - a2 - ie2 - ong3 - iang2 - ie1 - in4 - iao1 - e1 - in2 - en4 - uan3 - "\xFC2" - ing3 - i - ei2 - ei3 - iang1 - er2 - ia4 - uo2 - "\xFC3" - uan1 - ia1 - e3 - ong4 - ie4 - ai1 - en3 - iang3 - eng4 - iang4 - ao1 - ou1 - ang2 - ai3 - iu4 - "\xFCan2" - ang3 - en1 - ong2 - uei4 - ei4 - iao3 - "\xFC4" - an2 - ing4 - an3 - a3 - ie3 - an1 - ian3 - uo1 - ing1 - ou4 - ian1 - ou3 - eng1 - ang1 - in1 - a4 - eng2 - uo4 - u1 - ang4 - iou3 - iao4 - ian2 - u2 - ui4 - e2 - en2 - u3 - ing2 - ao4 - ong1 - an4 - ai2 - ao3 - uo3 - ian4 - p - c - a1 - ai4 - e4 - s - k - r - i2 - f - n - u4 - ch - i3 - i1 - q - z - m - t - g - b - e - h - i4 - x - "\uFF0C" - zh - "\u3002" - l - j - sh - d - odim: null model_conf: {} use_preprocessor: true token_type: phn bpemodel: null non_linguistic_symbols: null cleaner: null g2p: pypinyin_g2p_phone feats_extract: fbank feats_extract_conf: fs: 24000 fmin: 80 fmax: 7600 n_mels: 80 hop_length: 300 n_fft: 2048 win_length: 1200 normalize: global_mvn normalize_conf: stats_file: exp/tts_stats_raw_phn_pypinyin_g2p_phone/train/feats_stats.npz tts: tacotron2 tts_conf: embed_dim: 512 elayers: 1 eunits: 512 econv_layers: 3 econv_chans: 512 econv_filts: 5 atype: location adim: 512 aconv_chans: 32 aconv_filts: 15 cumulate_att_w: true dlayers: 2 dunits: 1024 prenet_layers: 2 prenet_units: 256 postnet_layers: 5 postnet_chans: 512 postnet_filts: 5 output_activation: null use_batch_norm: true use_concate: true use_residual: false dropout_rate: 0.5 zoneout_rate: 0.1 reduction_factor: 1 spk_embed_dim: null use_masking: true bce_pos_weight: 5.0 use_guided_attn_loss: true guided_attn_loss_sigma: 0.4 guided_attn_loss_lambda: 1.0 required: - output_dir - token_list distributed: false</code></pre>