Diff-SVC

Overview

Diff-SVC is an open-source singing voice conversion tool utilizing diffusion models. It allows users to convert one singing voice into another. The architecture leverages diffusion probabilistic models to generate audio, offering capabilities to modify vocal characteristics such as pitch, timbre, and intonation. Key updates include support for 44.1kHz audio, optimizations for training speed and model size using the 'no_fs2' option, and improved inference. It supports various input and output audio formats. The project aims for academic exchange and is not intended for production environments, with no responsibility for copyright issues arising from generated content. Preprocessing, training, and inference instructions are provided, along with documentation for detailed parameter settings.

Common tasks

Voice Conversion Audio Synthesis Speech Modification

FAQ

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What is Diff-SVC?

Diff-SVC is a singing voice conversion tool that uses diffusion models to convert one singing voice into another.

Is Diff-SVC free to use?

Yes, Diff-SVC is an open-source project and is free to use.

What are the system requirements for Diff-SVC?

Diff-SVC requires Python 3.7 or higher, along with several Python packages. A GPU is recommended for faster training and inference.

How do I train a Diff-SVC model?

You can train a Diff-SVC model by following the instructions in the documentation. This involves preprocessing the audio data, configuring the training parameters, and running the training script.

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