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| { | |
| "base_config": "config/tts.json", | |
| "model_type": "VALLE", | |
| "task_type": "tts", | |
| "dataset": [ | |
| "libritts" | |
| ], | |
| "preprocess": { | |
| "extract_phone": true, | |
| "phone_extractor": "espeak", // phoneme extractor: espeak, pypinyin, pypinyin_initials_finals or lexicon | |
| "extract_acoustic_token": true, | |
| "acoustic_token_extractor": "Encodec", // acoustic token extractor: encodec, dac(todo) | |
| "acoustic_token_dir": "acoutic_tokens", | |
| "use_text": false, | |
| "use_phone": true, | |
| "use_acoustic_token": true, | |
| "symbols_dict": "symbols.dict", | |
| "min_duration": 0.5, // the duration lowerbound to filter the audio with duration < min_duration | |
| "max_duration": 14, // the duration uperbound to filter the audio with duration > max_duration. | |
| "sample_rate": 24000, | |
| "codec_hop_size": 320 | |
| }, | |
| "model": { | |
| "text_token_num": 512, | |
| "audio_token_num": 1024, | |
| "decoder_dim": 1024, // embedding dimension of the decoder model | |
| "nhead": 16, // number of attention heads in the decoder layers | |
| "num_decoder_layers": 12, // number of decoder layers | |
| "norm_first": true, // pre or post Normalization. | |
| "add_prenet": false, // whether add PreNet after Inputs | |
| "prefix_mode": 0, // mode for how to prefix VALL-E NAR Decoder, 0: no prefix, 1: 0 to random, 2: random to random, 4: chunk of pre or post utterance | |
| "share_embedding": true, // share the parameters of the output projection layer with the parameters of the acoustic embedding | |
| "nar_scale_factor": 1, // model scale factor which will be assigned different meanings in different models | |
| "prepend_bos": false, // whether prepend <BOS> to the acoustic tokens -> AR Decoder inputs | |
| "num_quantizers": 8, // numbert of the audio quantization layers | |
| // "scaling_xformers": false, // Apply Reworked Conformer scaling on Transformers | |
| }, | |
| "train": { | |
| "use_dynamic_batchsize": false, // If use dynamic batch size | |
| "ddp": false, | |
| "train_stage": 1, // 0: train all modules, For VALL_E, support 1: AR Decoder 2: NAR Decoder(s) | |
| "max_epoch": 20, | |
| "optimizer": "AdamW", | |
| "scheduler": "cosine", | |
| "warmup_steps": 16000, // number of steps that affects how rapidly the learning rate decreases | |
| "total_training_steps": 800000, | |
| "base_lr": 1e-4, // base learning rate." | |
| "valid_interval": 1000, | |
| "log_epoch_step": 1000, | |
| "save_checkpoint_stride": [ | |
| 1, | |
| 1 | |
| ] | |
| } | |
| } | |