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datasets: |
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- Wenetspeech4TTS/WenetSpeech4TTS |
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language: |
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- zh |
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--- |
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# ISCSLP2024 Conversational Voice Clone Challenge(CoVoC) baseline model. |
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There are two baseline models in this competition. |
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## VALL-E: |
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VALL-E is trained using [Amphion](https://github.com/open-mmlab/Amphion). |
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First, training is performed on the Wenetspeech4TTS dataset, and the model weight is valle_base_model.bin. |
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After that, fine-tuning is performed on the HQ-Conversations dataset, the model weight is valle_HQ-sft_model.bin. |
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For specific inference code, please refer to [ISCSLP2024_CoVoC_baseline Github](https://github.com/xkx-hub/ISCSLP2024_CoVoC_baseline) for more details. |
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## fish-speech: |
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An open-source speech model, fish-speech, whose LLAMA and vits_decoder are fine-tuned using the HQ-Conversations dataset. |
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The training follows the default configuration of fish-speech. |
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For specific training code, please refer to [Fish Speech Github](https://github.com/fishaudio/fish-speech) for more details. |
