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sprocket

Voice conversion software - Voice conversion (VC) is a technique to convert a speaker identity of a source speaker into that of a target speaker. This software enables the users to develop a traditional VC system based on a Gaussian mixture model (GMM) and a vocoder-free VC system based on a differential GMM (DIFFGMM) using a parallel dataset of the source and target speakers.

Paper and slide

Conversion samples

Purpose

Reproduce the typical VC systems

This software was developed to make it possible for the users to easily build the VC systems by only preparing a parallel dataset of the desired source and target speakers and executing example scripts. The following VC methods were implemented as the typical VC methods.

Traditional VC method based on GMM

Vocoder-free VC method based on DIFFGMM

Supply Python3 VC library

To make it possible to easily develop VC-based applications using Python (Python3), the VC library is also supplied, including several interfaces, such as acoustic feature analysis/synthesis, acoustic feature modeling, acoustic feature conversion, and waveform modification. For the details of the VC library, please see sprocket documents in (coming soon).

Installation & Run

Please use NOT Python2 BUT Python3.

Current stable version

Ver. 0.18.1

Install sprocket

pip install numpy==1.15.4 cython  # for dependency
pip install sprocket-vc

Run example

See VC example

REPORTING BUGS

For any questions or issues please visit:

https://github.com/k2kobayashi/sprocket/issues

COPYRIGHT

Copyright (c) 2017 Kazuhiro KOBAYASHI

Released under the MIT license

https://opensource.org/licenses/mit-license.php

ACKNOWLEDGEMENTS

Thank you @r9y9 and @tats-u for lots of contributions and encouragement helps before release.

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