This application is client software for real-time voice conversion that supports various voice conversion models. This document provides a description for voice conversion limited to [RVC(Retrieval-based-Voice-Conversion)](https://github.com/liujing04/Retrieval-based-Voice-Conversion-WebUI).
- If you want to learn by yourself, please go to [RVC(Retrieval-based-Voice-Conversion)](https://github.com/liujing04/Retrieval-based-Voice-Conversion-WebUI).
- [Recording app on Github Pages](https://w-okada.github.io/voice-changer/) is convenient for preparing voice for learning on the browser.
- [TIPS for training](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/docs/training_tips_en.md) has been published, so please refer to it.
Download `hubert_base.pt` from [this repository](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main) and store it in the folder containing the batch file.
After extracting the download file, execute `startHttp.command`. If it shows that the developer cannot be verified, press the control key again and click to execute (or right-click to execute).
This is the time it takes to convert data that is the sum of Input Chunk and Extra Data Length. Shortening both Input Chunk and Extra Data Length will reduce the number.
Get information held by the server. If information synchronization between server and client seems not to be successful, please press the Reload button.
If enable PyTorch is turned on, you can select the PyTorch model (extension is pth). If you turn this on when using a model converted from RVC, the PyTorch item will appear. (From the next version, you can only choose either PyTorch or ONNX for each slot.
Enter the default value for how much the pitch of the voice should be converted. You can also convert during inference. Below is a guideline for the settings.
As for the input, the sound of the microphone is sent to the server and recorded as it is. It can be used to check the communication path from the microphone to the server.
For output, the data output from the model is recorded in the server. You can see how the model behaves (once you've verified that your input is correct).
It seems to be a setting when supporting multiple speakers, but it is not used at present because the RVC head office does not support it (it is unlikely).
Decide how much length to cut and convert in one conversion. The higher the value, the more efficient the conversion, but the larger the buf value, the longer the maximum time before the conversion starts. The approximate time is displayed in buff:.
Determines how much past audio to include in the input when converting audio. The longer the past voice is, the better the accuracy of the conversion, but the longer the res is, the longer the calculation takes.
(Probably because Transformer is a bottleneck, the calculation time will increase by the square of this length)