README.md

metadata

license: cc-by-nc-sa-4.0
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  The Models are available for download for non-commercial purposes .  Terms of
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datasets:
  - Wenetspeech4TTS/WenetSpeech4TTS
language:
  - zh

ISCSLP2024 Conversational Voice Clone Challenge(CoVoC) baseline model.

There are two baseline models in this competition.

VALL-E:

VALL-E is trained using Amphion.

First, training is performed on the Wenetspeech4TTS dataset, and the model weight is valle_base_model.bin.

After that, fine-tuning is performed on the HQ-Conversations dataset, the model weight is valle_HQ-sft_model.bin.

For specific inference code, please refer to ISCSLP2024_CoVoC_baseline Github for more details.

fish-speech:

An open-source speech model, fish-speech, whose LLAMA and vits_decoder are fine-tuned using the HQ-Conversations dataset.

The training follows the default configuration of fish-speech.

For specific training code, please refer to Fish Speech Github for more details.