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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. | |
"sampling_rate": 24000, | |
}, | |
"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": { | |
"ddp": false, | |
"train_stage": 1, // 0: train all modules, For VALL_E, support 1: AR Decoder 2: NAR Decoder(s) | |
"max_epoch": 20, | |
"optimizer": "ScaledAdam", | |
"scheduler": "Eden", | |
"warmup_steps": 200, // number of steps that affects how rapidly the learning rate decreases | |
"base_lr": 0.05, // base learning rate." | |
"valid_interval": 1000, | |
"log_epoch_step": 1000, | |
"save_checkpoint_stride": [ | |
1, | |
1 | |
] | |
} | |
} |