lakahaga/novel_reading_tts

ESPnet2 TTS model

`lakahaga/novel_reading_tts`

This model was trained by lakahaga using novelspeech recipe in espnet.

Demo: How to use in ESPnet2

cd espnet git checkout 9827dfe37f69e8e55f902dc4e340de5108596311 pip install -e . cd egs2/novelspeech/tts1 ./run.sh --skip_data_prep false --skip_train true --download_model lakahaga/novel_reading_tts

TTS config

expand

config: conf/tuning/train_conformer_fastspeech2.yaml print_config: false log_level: INFO dry_run: false iterator_type: sequence output_dir: exp/tts_train_conformer_fastspeech2_raw_phn_tacotron_none ngpu: 1 seed: 0 num_workers: 1 num_att_plot: 3 dist_backend: nccl dist_init_method: env:// dist_world_size: 4 dist_rank: 0 local_rank: 0 dist_master_addr: localhost dist_master_port: 34177 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: 1000 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 nbest_averaging_interval: 0 grad_clip: 1.0 grad_clip_type: 2.0 grad_noise: false accum_grad: 10 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 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: 1000 batch_size: 20 valid_batch_size: null batch_bins: 25600000 valid_batch_bins: null train_shape_file: - exp/tts_train_raw_phn_tacotron_none/decode_use_teacher_forcingtrue_train.loss.best/stats//train/text_shape.phn - exp/tts_train_raw_phn_tacotron_none/decode_use_teacher_forcingtrue_train.loss.best/stats//train/speech_shape valid_shape_file: - exp/tts_train_raw_phn_tacotron_none/decode_use_teacher_forcingtrue_train.loss.best/stats//valid/text_shape.phn - exp/tts_train_raw_phn_tacotron_none/decode_use_teacher_forcingtrue_train.loss.best/stats//valid/speech_shape batch_type: numel valid_batch_type: null fold_length: - 150 - 204800 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 - - exp/tts_train_raw_phn_tacotron_none/decode_use_teacher_forcingtrue_train.loss.best/tr_no_dev/durations - durations - text_int - - dump/raw/tr_no_dev/wav.scp - speech - sound - - exp/tts_train_raw_phn_tacotron_none/decode_use_teacher_forcingtrue_train.loss.best/stats//train/collect_feats/pitch.scp - pitch - npy - - exp/tts_train_raw_phn_tacotron_none/decode_use_teacher_forcingtrue_train.loss.best/stats//train/collect_feats/energy.scp - energy - npy - - dump/raw/tr_no_dev/utt2sid - sids - text_int valid_data_path_and_name_and_type: - - dump/raw/dev/text - text - text - - exp/tts_train_raw_phn_tacotron_none/decode_use_teacher_forcingtrue_train.loss.best/dev/durations - durations - text_int - - dump/raw/dev/wav.scp - speech - sound - - exp/tts_train_raw_phn_tacotron_none/decode_use_teacher_forcingtrue_train.loss.best/stats//valid/collect_feats/pitch.scp - pitch - npy - - exp/tts_train_raw_phn_tacotron_none/decode_use_teacher_forcingtrue_train.loss.best/stats//valid/collect_feats/energy.scp - energy - npy - - dump/raw/dev/utt2sid - sids - text_int allow_variable_data_keys: false max_cache_size: 0.0 max_cache_fd: 32 valid_max_cache_size: null optim: adam optim_conf: lr: 1.0 scheduler: noamlr scheduler_conf: model_size: 384 warmup_steps: 4000 token_list: - <blank> - <unk> - '=' - _ - A - Y - N - O - E - U - L - G - S - D - M - J - H - B - ZERO - TWO - C - . - Q - ',' - P - T - SEVEN - X - W - THREE - ONE - NINE - K - EIGHT - '@' - '!' - Z - '?' - F - SIX - FOUR - '#' - $ - + - '%' - FIVE - '~' - AND - '*' - '...' - '' - ^ - <sos/eos> odim: null model_conf: {} use_preprocessor: true token_type: phn bpemodel: null non_linguistic_symbols: null cleaner: tacotron g2p: null feats_extract: fbank feats_extract_conf: n_fft: 1024 hop_length: 256 win_length: null fs: 22050 fmin: 80 fmax: 7600 n_mels: 80 normalize: global_mvn normalize_conf: stats_file: exp/tts_train_raw_phn_tacotron_none/decode_use_teacher_forcingtrue_train.loss.best/stats//train/feats_stats.npz tts: fastspeech2 tts_conf: adim: 384 aheads: 2 elayers: 4 eunits: 1536 dlayers: 4 dunits: 1536 positionwise_layer_type: conv1d positionwise_conv_kernel_size: 3 duration_predictor_layers: 2 duration_predictor_chans: 256 duration_predictor_kernel_size: 3 postnet_layers: 5 postnet_filts: 5 postnet_chans: 256 use_masking: true encoder_normalize_before: true decoder_normalize_before: true reduction_factor: 1 encoder_type: conformer decoder_type: conformer conformer_pos_enc_layer_type: rel_pos conformer_self_attn_layer_type: rel_selfattn conformer_activation_type: swish use_macaron_style_in_conformer: true use_cnn_in_conformer: true conformer_enc_kernel_size: 7 conformer_dec_kernel_size: 31 init_type: xavier_uniform transformer_enc_dropout_rate: 0.2 transformer_enc_positional_dropout_rate: 0.2 transformer_enc_attn_dropout_rate: 0.2 transformer_dec_dropout_rate: 0.2 transformer_dec_positional_dropout_rate: 0.2 transformer_dec_attn_dropout_rate: 0.2 pitch_predictor_layers: 5 pitch_predictor_chans: 256 pitch_predictor_kernel_size: 5 pitch_predictor_dropout: 0.5 pitch_embed_kernel_size: 1 pitch_embed_dropout: 0.0 stop_gradient_from_pitch_predictor: true energy_predictor_layers: 2 energy_predictor_chans: 256 energy_predictor_kernel_size: 3 energy_predictor_dropout: 0.5 energy_embed_kernel_size: 1 energy_embed_dropout: 0.0 stop_gradient_from_energy_predictor: false pitch_extract: dio pitch_extract_conf: fs: 22050 n_fft: 1024 hop_length: 256 f0max: 400 f0min: 80 reduction_factor: 1 pitch_normalize: global_mvn pitch_normalize_conf: stats_file: exp/tts_train_raw_phn_tacotron_none/decode_use_teacher_forcingtrue_train.loss.best/stats//train/pitch_stats.npz energy_extract: energy energy_extract_conf: fs: 22050 n_fft: 1024 hop_length: 256 win_length: null reduction_factor: 1 energy_normalize: global_mvn energy_normalize_conf: stats_file: exp/tts_train_raw_phn_tacotron_none/decode_use_teacher_forcingtrue_train.loss.best/stats//train/energy_stats.npz required: - output_dir - token_list version: 0.10.5a1 distributed: true

Citing ESPnet

@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} } @inproceedings{hayashi2020espnet, title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit}, author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu}, booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, pages={7654--7658}, year={2020}, organization={IEEE} }

or arXiv:
@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} }

数据统计

数据评估

lakahaga/novel_reading_tts浏览人数已经达到15，如你需要查询该站的相关权重信息，可以点击"5118数据""爱站数据""Chinaz数据"进入；以目前的网站数据参考，建议大家请以爱站数据为准，更多网站价值评估因素如：lakahaga/novel_reading_tts的访问速度、搜索引擎收录以及索引量、用户体验等；当然要评估一个站的价值，最主要还是需要根据您自身的需求以及需要，一些确切的数据则需要找lakahaga/novel_reading_tts的站长进行洽谈提供。如该站的IP、PV、跳出率等！

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