--- tags: - espnet - audio - singing-voice-synthesis language: jp datasets: - oniku_kurumi_utagoe_db license: cc-by-4.0 --- ## ESPnet2 SVS model ### `espnet/oniku_kurumi_utagoe_db_svs_visinger2` This model was trained by ftshijt using oniku_kurumi_utagoe_db 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 5c4d7cf7feba8461de2e1080bf82182f0efaef38 pip install -e . cd egs2/oniku_kurumi_utagoe_db/svs1 ./run.sh --skip_data_prep false --skip_train true --download_model espnet/oniku_kurumi_utagoe_db_svs_visinger2 ``` ## SVS config
expand ``` config: conf/tuning/train_visinger2.yaml print_config: false log_level: INFO drop_last_iter: false dry_run: false iterator_type: sequence valid_iterator_type: null output_dir: 44kexp/svs_train_visinger2_raw_phn_pyopenjtalk_jp ngpu: 1 seed: 777 num_workers: 4 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: true sharded_ddp: false cudnn_enabled: true cudnn_benchmark: false cudnn_deterministic: false collect_stats: false write_collected_feats: false max_epoch: 500 patience: null val_scheduler_criterion: - valid - loss early_stopping_criterion: - valid - loss - min best_model_criterion: - - train - total_count - max keep_nbest_models: 10 nbest_averaging_interval: 0 grad_clip: -1 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: 50 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_lora: false save_lora_only: true lora_conf: {} pretrain_path: null init_param: [] ignore_init_mismatch: false freeze_param: [] num_iters_per_epoch: 1000 batch_size: 8 valid_batch_size: null batch_bins: 1000000 valid_batch_bins: null train_shape_file: - 44kexp/svs_stats_raw_phn_pyopenjtalk_jp/train/text_shape.phn - 44kexp/svs_stats_raw_phn_pyopenjtalk_jp/train/singing_shape valid_shape_file: - 44kexp/svs_stats_raw_phn_pyopenjtalk_jp/valid/text_shape.phn - 44kexp/svs_stats_raw_phn_pyopenjtalk_jp/valid/singing_shape batch_type: sorted valid_batch_type: null fold_length: - 150 - 409600 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: - - 44kdump/raw/tr_no_dev/text - text - text - - 44kdump/raw/tr_no_dev/wav.scp - singing - sound - - 44kdump/raw/tr_no_dev/label - label - duration - - 44kdump/raw/tr_no_dev/score.scp - score - score valid_data_path_and_name_and_type: - - 44kdump/raw/dev/text - text - text - - 44kdump/raw/dev/wav.scp - singing - sound - - 44kdump/raw/dev/label - label - duration - - 44kdump/raw/dev/score.scp - score - score 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: adamw optim_conf: lr: 0.0002 betas: - 0.8 - 0.99 eps: 1.0e-09 weight_decay: 0.0 scheduler: exponentiallr scheduler_conf: gamma: 0.998 optim2: adamw optim2_conf: lr: 0.0002 betas: - 0.8 - 0.99 eps: 1.0e-09 weight_decay: 0.0 scheduler2: exponentiallr scheduler2_conf: gamma: 0.998 generator_first: false token_list: - - - pau - a - o - i - u - e - k - n - r - m - t - N - s - w - y - sh - g - d - ch - b - ts - p - z - h - f - j - cl - ry - ky - gy - ny - hy - my - v - by - py - ty - dy - odim: null model_conf: {} use_preprocessor: true token_type: phn bpemodel: null non_linguistic_symbols: null cleaner: null g2p: pyopenjtalk fs: 44100 score_feats_extract: syllable_score_feats score_feats_extract_conf: fs: 44100 n_fft: 2048 win_length: 2048 hop_length: 512 feats_extract: fbank feats_extract_conf: n_fft: 2048 hop_length: 512 win_length: 2048 fs: 44100 fmin: 80 fmax: 22050 n_mels: 80 normalize: global_mvn normalize_conf: stats_file: 44kexp/svs_stats_raw_phn_pyopenjtalk_jp/train/feats_stats.npz svs: vits svs_conf: generator_type: visinger2 vocoder_generator_type: visinger2 generator_params: hidden_channels: 192 spks: -1 global_channels: -1 segment_size: 20 text_encoder_attention_heads: 2 text_encoder_ffn_expand: 4 text_encoder_blocks: 6 text_encoder_positionwise_layer_type: conv1d text_encoder_positionwise_conv_kernel_size: 3 text_encoder_positional_encoding_layer_type: rel_pos text_encoder_self_attention_layer_type: rel_selfattn text_encoder_activation_type: swish text_encoder_normalize_before: true text_encoder_dropout_rate: 0.1 text_encoder_positional_dropout_rate: 0.0 text_encoder_attention_dropout_rate: 0.1 use_macaron_style_in_text_encoder: true use_conformer_conv_in_text_encoder: false text_encoder_conformer_kernel_size: -1 decoder_kernel_size: 7 decoder_channels: 256 decoder_upsample_scales: - 8 - 8 - 4 - 2 decoder_upsample_kernel_sizes: - 16 - 16 - 8 - 4 n_harmonic: 64 decoder_resblock_kernel_sizes: - 3 - 7 - 11 decoder_resblock_dilations: - - 1 - 3 - 5 - - 1 - 3 - 5 - - 1 - 3 - 5 use_weight_norm_in_decoder: true posterior_encoder_kernel_size: 3 posterior_encoder_layers: 8 posterior_encoder_stacks: 1 posterior_encoder_base_dilation: 1 posterior_encoder_dropout_rate: 0.0 use_weight_norm_in_posterior_encoder: true flow_flows: -1 flow_kernel_size: 5 flow_base_dilation: 1 flow_layers: 4 flow_dropout_rate: 0.0 use_weight_norm_in_flow: true use_only_mean_in_flow: true use_phoneme_predictor: false vocabs: 41 aux_channels: 80 generator_type: visinger2 vocoder_generator_type: visinger2 fs: 44100 hop_length: 512 win_length: 2048 n_fft: 2048 discriminator_type: visinger2 discriminator_params: scales: 1 scale_downsample_pooling: AvgPool1d scale_downsample_pooling_params: kernel_size: 4 stride: 2 padding: 2 scale_discriminator_params: in_channels: 1 out_channels: 1 kernel_sizes: - 15 - 41 - 5 - 3 channels: 128 max_downsample_channels: 1024 max_groups: 256 bias: true downsample_scales: - 4 - 4 - 4 - 4 nonlinear_activation: LeakyReLU nonlinear_activation_params: negative_slope: 0.1 use_weight_norm: true use_spectral_norm: false follow_official_norm: false periods: - 2 - 3 - 5 - 7 - 11 period_discriminator_params: in_channels: 1 out_channels: 1 kernel_sizes: - 5 - 3 channels: 32 downsample_scales: - 3 - 3 - 3 - 3 - 1 max_downsample_channels: 1024 bias: true nonlinear_activation: LeakyReLU nonlinear_activation_params: negative_slope: 0.1 use_weight_norm: true use_spectral_norm: false multi_freq_disc_params: hidden_channels: - 256 - 256 - 256 - 256 - 256 domain: double mel_scale: true divisors: - 32 - 16 - 8 - 4 - 2 - 1 - 1 strides: - 1 - 2 - 1 - 2 - 1 - 2 - 1 sample_rate: 44100 hop_lengths: - 110 - 220 - 330 - 441 - 551 - 661 generator_adv_loss_params: average_by_discriminators: false loss_type: mse discriminator_adv_loss_params: average_by_discriminators: false loss_type: mse feat_match_loss_params: average_by_discriminators: false average_by_layers: false include_final_outputs: true mel_loss_params: fs: 44100 n_fft: 2048 hop_length: 512 win_length: 2048 window: hann n_mels: 80 fmin: 0 fmax: 22050 log_base: null lambda_adv: 1.0 lambda_mel: 45.0 lambda_feat_match: 2.0 lambda_dur: 0.1 lambda_pitch: 10.0 lambda_phoneme: 1.0 lambda_kl: 1.0 sampling_rate: 44100 cache_generator_outputs: true pitch_extract: dio pitch_extract_conf: use_token_averaged_f0: false use_log_f0: false fs: 44100 n_fft: 2048 hop_length: 512 f0max: 800 f0min: 80 pitch_normalize: null pitch_normalize_conf: stats_file: 44kexp/svs_stats_raw_phn_pyopenjtalk_jp/train/pitch_stats.npz ying_extract: null ying_extract_conf: {} energy_extract: null energy_extract_conf: {} energy_normalize: null energy_normalize_conf: {} required: - output_dir - token_list version: '202310' 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{shi22d_interspeech, author={Jiatong Shi and Shuai Guo and Tao Qian and Tomoki Hayashi and Yuning Wu and Fangzheng Xu and Xuankai Chang and Huazhe Li and Peter Wu and Shinji Watanabe and Qin Jin}, title={{Muskits: an End-to-end Music Processing Toolkit for Singing Voice Synthesis}}, year=2022, booktitle={Proc. Interspeech 2022}, pages={4277--4281}, doi={10.21437/Interspeech.2022-10039} } ``` 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} } ```