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Yurii Paniv
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Parent(s):
b547cb7
Initial model
Browse files- README.md +24 -2
- config.json +158 -0
- requirements.txt +1 -0
README.md
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#
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Ukrainian TTS (text-to-speech) using Coqui TTS
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# Ukrainian TTS π’π€
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Ukrainian TTS (text-to-speech) using Coqui TTS.
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Trained on [M-AILABS Ukrainian dataset](https://www.caito.de/2019/01/the-m-ailabs-speech-dataset/).
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# How to use :
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1. `pip install -r requirements.txt`.
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2. Download model from "Releases" tab.
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3. Launch as one-time command:
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```
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tts --text "Text for TTS" \
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--model_path path/to/model.pth.tar \
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--config_path path/to/config.json \
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--out_path folder/to/save/output.wav
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```
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or alternatively launch web server using:
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```
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tts-server --model_path path/to/model.pth.tar \
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--config_path path/to/config.json
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```
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# How to train:
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1. Refer to ["Nervous beginner guide"](https://tts.readthedocs.io/en/latest/tutorial_for_nervous_beginners.html) in Coqui TTS docs.
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2. Instead of provided `config.json` use one from this repo.
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config.json
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{
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"model": "glow_tts",
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"run_name": "coqui_tts",
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"run_description": "",
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"epochs": 1000,
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"batch_size": 32,
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"eval_batch_size": 16,
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"mixed_precision": true,
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"scheduler_after_epoch": false,
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"run_eval": true,
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"test_delay_epochs": -1,
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"print_eval": true,
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"dashboard_logger": "tensorboard",
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"print_step": 25,
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"plot_step": 100,
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"model_param_stats": false,
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"project_name": null,
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"log_model_step": null,
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"wandb_entity": null,
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"save_step": 10000,
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"checkpoint": true,
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"keep_all_best": false,
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"keep_after": 10000,
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"num_loader_workers": 1,
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"num_eval_loader_workers": 1,
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"use_noise_augment": false,
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"output_path": "./ukrainian",
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"distributed_backend": "nccl",
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"distributed_url": "tcp://localhost:54321",
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"audio": {
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"fft_size": 1024,
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"win_length": 1024,
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"hop_length": 256,
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"frame_shift_ms": null,
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"frame_length_ms": null,
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"stft_pad_mode": "reflect",
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"sample_rate": 16000,
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"resample": false,
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"preemphasis": 0.0,
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"ref_level_db": 20,
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"do_sound_norm": false,
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"log_func": "np.log10",
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"do_trim_silence": true,
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"trim_db": 45,
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"power": 1.5,
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"griffin_lim_iters": 60,
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"num_mels": 80,
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"mel_fmin": 0.0,
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"mel_fmax": null,
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"spec_gain": 20,
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"do_amp_to_db_linear": true,
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"do_amp_to_db_mel": true,
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"signal_norm": true,
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"min_level_db": -100,
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"symmetric_norm": true,
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"max_norm": 4.0,
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"clip_norm": true,
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"stats_path": null
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},
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"use_phonemes": false,
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"use_espeak_phonemes": false,
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"phoneme_language": null,
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"compute_input_seq_cache": false,
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"text_cleaner": "basic_cleaners",
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"enable_eos_bos_chars": false,
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"test_sentences_file": "",
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"phoneme_cache_path": "./phoneme_cache",
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"characters": {
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"pad": "_",
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"eos": "~",
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"bos": "^",
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"characters": "!',-.:;?ABIMXaceinoprxy\u0404\u0406\u0407\u0410\u0411\u0412\u0413\u0414\u0415\u0416\u0417\u0418\u0419\u041a\u041b\u041c\u041d\u041e\u041f\u0420\u0421\u0422\u0423\u0424\u0425\u0426\u0427\u0428\u0429\u042c\u042f\u0430\u0431\u0432\u0433\u0434\u0435\u0436\u0437\u0438\u0439\u043a\u043b\u043c\u043d\u043e\u043f\u0440\u0441\u0442\u0443\u0444\u0445\u0446\u0447\u0448\u0449\u044c\u044e\u044f\u0454\u0456\u0457\u0490\u0491 ",
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"punctuations": "!',-.:;? ",
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"phonemes": null,
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"unique": true
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},
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"batch_group_size": 0,
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"loss_masking": null,
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"sort_by_audio_len": false,
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"min_seq_len": 3,
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"max_seq_len": 500,
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"compute_f0": false,
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"compute_linear_spec": false,
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"add_blank": false,
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"datasets": [
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{
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"name": "ljspeech",
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"path": "./data/uk_UK/by_book/female/sumska/kaydasheva",
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"meta_file_train": "metadata.csv",
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"ununsed_speakers": null,
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"meta_file_val": "",
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"meta_file_attn_mask": ""
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},
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{
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"name": "ljspeech",
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"path": "./data/uk_UK/by_book/female/sumska/mykola_djerya",
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"meta_file_train": "metadata.csv",
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"ununsed_speakers": null,
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"meta_file_val": "",
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"meta_file_attn_mask": ""
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}
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],
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"optimizer": "RAdam",
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"optimizer_params": {
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"betas": [
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0.9,
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0.998
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],
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"weight_decay": 1e-06
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},
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"lr_scheduler": "NoamLR",
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"lr_scheduler_params": {
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"warmup_steps": 4000
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},
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"test_sentences": [
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"\u0413\u043e\u0432\u043e\u0440\u0438 \u043d\u0456\u0431\u0438 \u0442\u0438 \u0436\u0438\u0432\u0438\u0439!",
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"\u041f\u043e\u043b \u043f\u0435\u0440\u0435\u0442\u043d\u0443\u0432 \u043f\u0443\u0441\u0442\u0435\u043b\u044e",
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"\u041f\u0440\u0438\u0432\u0456\u0442, \u0441\u0432\u0456\u0442\u0435!"
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],
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"use_speaker_embedding": false,
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"use_d_vector_file": false,
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"d_vector_dim": 0,
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"num_chars": null,
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"encoder_type": "rel_pos_transformer",
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"encoder_params": {
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"kernel_size": 3,
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"dropout_p": 0.1,
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"num_layers": 6,
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"num_heads": 2,
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"hidden_channels_ffn": 768,
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"input_length": null
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},
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"use_encoder_prenet": true,
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"hidden_channels_enc": 192,
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"hidden_channels_dec": 192,
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"hidden_channels_dp": 256,
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"dropout_p_dp": 0.1,
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"dropout_p_dec": 0.05,
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"mean_only": true,
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"out_channels": 80,
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"num_flow_blocks_dec": 12,
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"inference_noise_scale": 0.0,
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"kernel_size_dec": 5,
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"dilation_rate": 1,
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"num_block_layers": 4,
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"num_speakers": 0,
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"c_in_channels": 0,
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"num_splits": 4,
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"num_squeeze": 2,
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"sigmoid_scale": false,
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"data_dep_init_steps": 10,
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"style_wav_for_test": null,
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"length_scale": 1.0,
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"d_vector_file": false,
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"grad_clip": 5.0,
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"lr": 0.001,
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"r": 1
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}
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requirements.txt
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TTS==0.3.1
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