Metadata-Version: 2.1
Name: sprocket-vc
Version: 0.18.4
Summary: Voice conversion software
Home-page: https://github.com/k2kobayashi/sprocket
Author: Kazuhiro Kobayashi
Author-email: root.4mac@gmail.com
License: MIT
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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
        - K. Kobayashi, T. Toda, "sprocket: Open-Source Voice Conversion Software," Proc. Odyssey, pp. 203-210, June 2018.
        [[paper]](https://nuss.nagoya-u.ac.jp/s/h8YKnq6qxjjxtU3)
        
        - T. Toda, "Hands on Voice Conversion," Speech Processing Courses in Crete (SPCC), July 2018.
        [[slide]](https://www.slideshare.net/NU_I_TODALAB/hands-on-voice-conversion)
        
        ## Conversion samples
        - Voice Conversion Challenge 2018
        	- [HUB Task](https://nuss.nagoya-u.ac.jp/s/3F8dxTcdQdXir9s)
        	- [SPOKE Task](https://nuss.nagoya-u.ac.jp/s/ixwxa6DxYa68y4N)
        
        ## 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 Python3.
        
        ### Current stable version
        
        Ver. 0.18.4
        
        ### Install sprocket
        
        ```
        pip install numpy==1.15.4 cython  # for dependency
        pip install sprocket-vc
        ```
        
        ### Run example
        
        See [VC example](docs/vc_example.md)
        
        ## REPORTING BUGS
        
        For any questions or issues please visit:
        
        ```
        https://github.com/k2kobayashi/sprocket/issues
        ```
        
        ## COPYRIGHT
        
        Copyright (c) 2020 Kazuhiro KOBAYASHI
        
        Released under the MIT license
        
        [https://opensource.org/licenses/mit-license.php](https://opensource.org/licenses/mit-license.php)
        
        ## ACKNOWLEDGEMENTS
        Thank you [@r9y9](https://github.com/r9y9) and [@tats-u](https://github.com/tats-u) for lots of contributions and encouragement helps before release.
        
        ## Who we are
        - Kazuhiro Kobayashi [@k2kobayashi](https://github.com/k2kobayashi) [maintainer, design and development]
        
        - [Tomoki Toda](https://sites.google.com/site/tomokitoda/) [advisor]
        
        Changelog
        =========
        
        0.18.4 (2020/12/02)
        ------------------
        
        - Support new api for dependency library
        
        0.18.3 (2019/04/24)
        ------------------
        
        - Implement several functions for GMM-based VC and minor bugfix
        - #133
        - #132
        - #130
        - #127
        
        0.18 (2017/10/01)
        ------------------
        
         - Release first ver.
         - Baseline system for [Voice Conversion Challenge 2018](http://www.vc-challenge.org/)
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Multimedia :: Sound/Audio :: Speech
Requires-Python: >=3.5
Description-Content-Type: text/markdown
Provides-Extra: develop
