Difference between revisions of "Software"
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|GMM (Full Cov.), SGMM, DNN | |GMM (Full Cov.), SGMM, DNN | ||
|HLDA, STC, MLLT, MLLR, CMLLR (w/ reg. trees), Exponential transform | |HLDA, STC, MLLT, MLLR, CMLLR (w/ reg. trees), Exponential transform | ||
| − | | | + | |aligment, N-best, lattice rescoring (uses OpenFST) |
|Baum-Welch, MMI (boosted), MC, feature-based, sequence training | |Baum-Welch, MMI (boosted), MC, feature-based, sequence training | ||
|{{yes|Yes}} | |{{yes|Yes}} | ||
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|GMM, Tied-Mix, Exemplar based | |GMM, Tied-Mix, Exemplar based | ||
|CMLLR | |CMLLR | ||
| − | |aligment, N-best, lattice rescoring, | + | |aligment, N-best, lattice rescoring, parallel latices |
|Baum-Welch | |Baum-Welch | ||
|{{dunno}} | |{{dunno}} | ||
Revision as of 11:24, 3 September 2014
This page provides software grouped by application.
Contents
Automatic speech recognition
| ASR engines | General attributes | Programming | Implemented ASR techniques | Reproducible research | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| release / update | actively developed | licence | platforms | links | extensions | language | hardware optimization | VAD | acoustic features | feature normalization / compensation | acoustic models | model adaptation / compensation | decoding techniques | training techniques | online ASR | training recipes | reproducible results | |
| CMU Sphinx | 1986-* (Sphinx 4.1.0, pocketsphinx 0.8) | Yes | proprietary, allows modif. | Windows, Linux, OSX (Sphinx4) / Raspberry-pi, iPhone, Android (pocketsphinx) | website | Java (Sphinx4), C (pocketsphinx) | No | Yes | MFCC, PLP | CMN, Mel-Spectrum subtraction | GMM, Streams | MLLR, MAP | aligment, N-best, lattice rescoring | Baum-Welch | Yes | AURORA4 (WSJ0) | ||
| HTK | 1993-2009 (3.4.1) | No | proprietary | Windows, Linux, OSX | website | official, ATK, uncertainty decoding | C | No | Yes | MFCC, PLP | VTLN, CMN | GMM (Full Cov.), Tied-Mix, Streams | HLDA, MLLR (w/ reg. trees), CMLR (w/ adaptive training), MAP | aligment, N-best, lattice rescoring | Baum-Welch | Yes | AURORA2 (purch.) AURORA3 (purch.), AURORA4 (WSJ0), CHIME-1, CHIME-2-I, REVERB | ETSI-AFE-AURORA2 paper (see AURORA2 purch.) |
| Kaldi | 2009-* (continous updates) | Yes | Apache 2.0 | Windows (not mantained as of 2014), Linux, OSX | website | C++ | BLAS, LAPACK, GPU (for DNNs) | Yes | MFCC, PLP | VTLN, CMVN | GMM (Full Cov.), SGMM, DNN | HLDA, STC, MLLT, MLLR, CMLLR (w/ reg. trees), Exponential transform | aligment, N-best, lattice rescoring (uses OpenFST) | Baum-Welch, MMI (boosted), MC, feature-based, sequence training | Yes | AURORA4 (WSJ0), CHIME-2 | Weniger2014-REVERB Paper Code | |
| Spraak | 2012 (1.1) | No | proprietary | Windows (limited), Linux | website | C, Python | No | Yes | MFCC, PLP | VTLN,CMN, MIDA, MDT Techniques | GMM, Tied-Mix, Exemplar based | CMLLR | aligment, N-best, lattice rescoring, parallel latices | Baum-Welch | ? | AURORA4 | ||
Speaker identification and verification
Speech enhancement and separation
Other applications
Contribute software
To contribute new software, please
- create an account and login
- go to the wiki page above corresponding to your application; if it does not exist yet, you may create it
- click on the "Edit" link at the top of the page and add a new section for your software (software is ordered by year of the latest version)
- click on the "Save page" link at the bottom of the page to save your modifications
Please make sure to provide the following information:
- name of the software and year of the latest version
- authors, institution, contact information
- link to the software, ideally including a short demo, and to the external libraries needed
- short description (functionalities, inputs and outputs, programming language, operating system, license, etc) and link to a paper/report describing the software, if any
- whether running on well-known baselines (Aurora-2, Aurora-4, Switchboard, CHiME, etc) is included or requires wrapping by the user
In order to save storage space, please do not upload the software on this wiki, but link it as much as possible from a public repository (e.g., bitbucket, github, sourceforge) or from a stable URL on the website of your institution. If this is not possible, please contact the resources sharing working group.
