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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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> Please look forward to the pretrained base model of RVCv3, which has larger parameters, larger data, better results, unchanged inference speed, and requires less training data for training.
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## Summary
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This repository has the following features:
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+ Reduce tone leakage by replacing the source feature to training-set feature using top1 retrieval;
@@ -42,6 +41,7 @@ This repository has the following features:
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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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+ Use the most powerful High-pitch Voice Extraction Algorithm [InterSpeech2023-RMVPE](#Credits) to prevent the muted sound problem. Provides the best results (significantly) and is faster, with even lower resource consumption than Crepe_full.
If you want to use the latest SOTA RMVPE vocal pitch extraction algorithm, you need to download the RMVPE weights and place them in the RVC root directory
If you are using Windows or macOS, you can download and extract `RVC-beta.7z` to use RVC directly by using `go-web.bat` on windows or `sh ./run.sh` on macOS to start Webui.
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There's also a tutorial on RVC in Chinese and you can check it out if needed.
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