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        "author": "Kazuhiro Kobayashi",
        "author_email": "root.4mac@gmail.com",
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            "License :: OSI Approved :: MIT License",
            "Topic :: Multimedia :: Sound/Audio :: Speech"
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        "description": "[![Python Version](https://img.shields.io/badge/Python-3.5%2C%203.6%2C%203.7-green.svg)](https://img.shields.io/badge/Python-3.5%2C%203.6%2C%203.7-green.svg)\n[![Build Status](https://www.travis-ci.org/k2kobayashi/sprocket.svg?branch=travis)](https://www.travis-ci.org/k2kobayashi/sprocket)\n[![Coverage Status](https://coveralls.io/repos/github/k2kobayashi/sprocket/badge.svg?branch=master)](https://coveralls.io/github/k2kobayashi/sprocket?branch=master)\n[![PyPI version](https://badge.fury.io/py/sprocket-vc.svg)](https://badge.fury.io/py/sprocket-vc)\n[![MIT License](http://img.shields.io/badge/license-MIT-blue.svg?style=flat)](LICENSE)\n\nsprocket\n======\n\n\nVoice 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.\n\n## Paper and slide\n- K. Kobayashi, T. Toda, \"sprocket: Open-Source Voice Conversion Software,\" Proc. Odyssey, pp. 203-210, June 2018.\n[[paper]](https://nuss.nagoya-u.ac.jp/s/h8YKnq6qxjjxtU3)\n\n- T. Toda, \"Hands on Voice Conversion,\" Speech Processing Courses in Crete (SPCC), July 2018.\n[[slide]](https://www.slideshare.net/NU_I_TODALAB/hands-on-voice-conversion)\n\n## Conversion samples\n- Voice Conversion Challenge 2018 [[zip]](https://nuss.nagoya-u.ac.jp/index.php/s/Cs0YbTCw85p3QDK)\n\n\n## Purpose\n### Reproduce the typical VC systems\n\nThis 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.\nThe following VC methods were implemented as the typical VC methods.\n\n#### Traditional VC method based on GMM\n- 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.\n\n#### Vocoder-free VC method based on DIFFGMM\n- 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.\n\n### Supply Python3 VC library\nTo 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.\nFor the details of the VC library, please see sprocket documents in (coming soon).\n\n## Installation & Run\n\nPlease use NOT Python2 BUT Python3.\n\n### Current stable version\n\nVer. 0.18.1\n\n### Install sprocket\n\n```\npip install numpy==1.15.4 cython  # for dependency\npip install sprocket-vc\n```\n\n### Run example\n\nSee [VC example](docs/vc_example.md)\n\n## REPORTING BUGS\n\nFor any questions or issues please visit:\n\n```\nhttps://github.com/k2kobayashi/sprocket/issues\n```\n\n## COPYRIGHT\n\nCopyright (c) 2017 Kazuhiro KOBAYASHI\n\nReleased under the MIT license\n\n[https://opensource.org/licenses/mit-license.php](https://opensource.org/licenses/mit-license.php)\n\n## ACKNOWLEDGEMENTS\nThank you [@r9y9](https://github.com/r9y9) and [@tats-u](https://github.com/tats-u) for lots of contributions and encouragement helps before release.\n\n## Who we are\n- Kazuhiro Kobayashi [@k2kobayashi](https://github.com/k2kobayashi) [maintainer, design and development]\n\n- [Tomoki Toda](https://sites.google.com/site/tomokitoda/) [advisor]\n\nChangelog\n=========\n\n0.18.3 (2019/04/24)\n------------------\n\n- Implement several functions for GMM-based VC and minor bugfix\n- #133\n- #132\n- #130\n- #127\n\n0.18 (2017/10/01)\n------------------\n\n - Release first ver.\n - Baseline system for [Voice Conversion Challenge 2018](http://www.vc-challenge.org/)\n\n\n",
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