so-vits-svc-fork 0.3.0

A fork of so-vits-svc.

SoftVC VITS Singing Voice Conversion Fork

A fork of so-vits-svc with a greatly improved interface. Based on branch 4.0 (v1). No differences in functionality and the models are compatible.

Installation

Install this via pip (or your favourite package manager):

pip install -U torch torchaudio --index-url https://download.pytorch.org/whl/cu117
pip install so-vits-svc-fork

Features not available in the original repo

• Realtime voice conversion
• GUI available
• Unified command-line interface (no need to run Python scripts)
• Ready to use just by installing with pip.
• Automatically download pretrained base model and HuBERT model
• Code completely formatted with black, isort, autoflake etc.

Usage

Inference

GUI

svcg

CLI

• Realtime (from microphone)

svc --model-path <model-path> source.wav

• File

svc vc --model-path <model-path>

Training

Colab notebook:

Place your dataset like dataset_raw/{speaker_id}/{wav_file}.wav and run:

svc pre-resample
svc pre-config
svc pre-hubert
svc train

Further help

For more details, run svc -h or svc <subcommand> -h.

svc -h
Usage: svc [OPTIONS] COMMAND [ARGS]...

  so-vits-svc allows any folder structure for training data. However, it is
  recommended to place the training data in the following structure:

      dataset_raw/{speaker_name}/{wav_name}.wav

  To train a model, run pre-resample, pre-config, pre-hubert, train. To infer
  a model, run infer.

Options:
  -h, --help  Show this message and exit.

Commands:
  clean         Clean up files, only useful if you are using the default...
  infer         Inference
  onnx          Export model to onnx
  pre-config    Preprocessing part 2: config
  pre-hubert    Preprocessing part 3: hubert
  pre-resample  Preprocessing part 1: resample
  train         Train model
  vc            Realtime inference from microphone

Contributors ✨

Thanks goes to these wonderful people (emoji key):

34j 💻 🤔 📖

This project follows the all-contributors specification. Contributions of any kind welcome!