/sprocket

Voice Conversion Tool Kit

Primary LanguagePythonMIT LicenseMIT

Python Version Build Status Coverage Status PyPI Version PyPI Downloads MIT License

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

  • K. Kobayashi, T. Toda, "sprocket: Open-Source Voice Conversion Software," Proc. Odyssey, June 2018. (To appear) [pdf]

Conversion samples

  • Voice Conversion Challenge 2018 [zip]

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

  • T. Toda, A.W. Black, K. Tokuda, "Voice conversion based on maximum likelihood estimation of spectral parameter trajectory," IEEE Transactions on Audio, Speech and Language Processing, Vol. 15, No. 8, pp. 2222-2235, Nov. 2007.

Vocoder-free VC method based on DIFFGMM

  • K. Kobayashi, T. Toda, S. Nakamura, "F0 transformation techniques for statistical voice conversion with direct waveform modification with spectral differential," Proc. IEEE SLT, pp. 693-700, Dec. 2016.

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

Install requirements

pip install numpy # for dependency
pip install -r requirements.txt

Install sprocket

python setup.py install

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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