--- tags: - espnet - audio - text-to-speech language: en datasets: - talromur license: cc-by-4.0 --- ## ESPnet2 TTS model ### `language-and-voice-lab/talromur_a_loudnorm_xvector_finetune_fastspeech2` This model was trained by G-Thor using talromur recipe in [espnet](https://github.com/espnet/espnet/). ### Demo: How to use in ESPnet2 Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html) if you haven't done that already. ```bash cd espnet git checkout d0047402e830a3c53e8b590064af4bf70415fb3b pip install -e . cd egs2/talromur/tts1 ./run.sh --skip_data_prep false --skip_train true --download_model language-and-voice-lab/talromur_a_loudnorm_xvector_finetune_fastspeech2 ``` ## TTS config
expand ``` config: ./conf/tuning/finetune_xvector_fastspeech2.yaml print_config: false log_level: INFO drop_last_iter: false dry_run: false iterator_type: sequence valid_iterator_type: null output_dir: exp/tts_finetune_a_loudnorm_xvector_fastspeech2 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 unused_parameters: false sharded_ddp: false cudnn_enabled: true cudnn_benchmark: false cudnn_deterministic: true collect_stats: false write_collected_feats: false max_epoch: 50 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: 8 no_forward_run: false resume: true train_dtype: float32 use_amp: false log_interval: null use_matplotlib: true use_tensorboard: true create_graph_in_tensorboard: false use_wandb: false wandb_project: null wandb_id: null wandb_entity: null wandb_name: null wandb_model_log_interval: -1 detect_anomaly: false use_adapter: false adapter: lora save_strategy: all adapter_conf: {} pretrain_path: null init_param: - /users/home/gunnaro/talromur_1and2_spk_avg_xvector_fastspeech2/exp/tts_xvector_fastspeech2_spk_avg_combined/valid.loss.ave_5best.pth:tts:tts ignore_init_mismatch: false freeze_param: [] num_iters_per_epoch: 800 batch_size: 20 valid_batch_size: null batch_bins: 4500000 valid_batch_bins: null train_shape_file: - exp/tts_stats_a/train/text_shape.phn - exp/tts_stats_a/train/speech_shape valid_shape_file: - exp/tts_stats_a/valid/text_shape.phn - exp/tts_stats_a/valid/speech_shape batch_type: numel valid_batch_type: null fold_length: - 150 - 204800 sort_in_batch: descending shuffle_within_batch: false sort_batch: descending multiple_iterator: false chunk_length: 500 chunk_shift_ratio: 0.5 num_cache_chunks: 1024 chunk_excluded_key_prefixes: [] chunk_default_fs: null train_data_path_and_name_and_type: - - dump/raw/train_a/text - text - text - - data/train_a/durations - durations - text_int - - dump/raw/train_a/wav.scp - speech - sound - - dump/xvector/train_a/xvector.scp - spembs - kaldi_ark valid_data_path_and_name_and_type: - - dump/raw/dev_a/text - text - text - - data/dev_a/durations - durations - text_int - - dump/raw/dev_a/wav.scp - speech - sound - - dump/xvector/dev_a/xvector.scp - spembs - kaldi_ark allow_variable_data_keys: false max_cache_size: 0.0 max_cache_fd: 32 allow_multi_rates: false valid_max_cache_size: null exclude_weight_decay: false exclude_weight_decay_conf: {} optim: adam optim_conf: lr: 0.1 scheduler: noamlr scheduler_conf: model_size: 384 warmup_steps: 4000 token_list: - - - a - r - sil - I - t - n - s - D - Y - E - l - v - m - h - k - j - G - T - f - p - 'E:' - c - i - 'au:' - 'O:' - 'a:' - ei - 'i:' - r_0 - t_h - O - k_h - ou - ai - '9' - au - 'I:' - 'ou:' - u - 'ei:' - N - l_0 - 'u:' - n_0 - '9:' - 'ai:' - 9i - c_h - p_h - x - C - '9i:' - 'Y:' - J - N_0 - m_0 - Oi - Yi - J_0 - spn - '1' - '7' - odim: null model_conf: {} use_preprocessor: true token_type: phn bpemodel: null non_linguistic_symbols: null cleaner: null 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_stats_a/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 use_scaled_pos_enc: true encoder_normalize_before: true decoder_normalize_before: true reduction_factor: 1 init_type: xavier_uniform init_enc_alpha: 1.0 init_dec_alpha: 1.0 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 spk_embed_dim: 512 spk_embed_integration_type: add 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_stats_a/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_stats_a/train/energy_stats.npz required: - output_dir - token_list version: '202402' distributed: false ```
### Citing ESPnet ```BibTex @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: ```bibtex @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} } ```