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@@ -24,6 +24,9 @@ An easy-to-use SVC framework based on VITS.<br><br>
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> Realtime Voice Conversion Software using RVC : [w-okada/voice-changer](https://github.com/w-okada/voice-changer)
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> The dataset for the pre-training model uses nearly 50 hours of high quality VCTK open source dataset.
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> High quality licensed song datasets will be added to training-set one after another for your use, without worrying about copyright infringement.
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## Summary
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This repository has the following features:
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+ Reduce tone leakage by replacing source feature to training-set feature using top1 retrieval;
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+ Supporting model fusion to change timbres (using ckpt processing tab->ckpt merge);
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+ Easy-to-use Webui interface;
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+ Use the UVR5 model to quickly separate vocals and instruments.
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+ The dataset for the pre-training model uses nearly 50 hours of high quality VCTK open source dataset, and high quality licensed song datasets will be added to training-set one after another for your use, without worrying about copyright infringement.
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## Preparing the environment
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We recommend you install the dependencies through poetry.
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pip install torch torchvision torchaudio
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#For Windows + Nvidia Ampere Architecture(RTX30xx), you need to specify the cuda version corresponding to pytorch according to the experience of https://github.com/liujing04/Retrieval-based-Voice-Conversion-WebUI/issues/21
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