Software

This page provides software grouped by application.

Automatic speech recognition

ASR engines	General attributes						Programming		Implemented techniques								Reproducible research
	release / update	actively developed	licence	platforms	links	extensions	language	hardware optimization	VAD	acoustic features	feature normalization	acoustic models	model adaptation	decoding techniques	training techniques	online ASR	robust ASR recipes	reproducible results
CMU Sphinx	1986-* (Sphinx 4.1.0, pocketsphinx 0.8)	Yes	BSD-like	Windows, Linux, OSX (Sphinx4) / Raspberry-pi, iPhone, Android (pocketsphinx)	website paper paper mail-list forum github		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)	Yes	proprietary	Windows, Linux, OSX	website book mail-list	official ATK uncertain features diagonal uncertainty decoding full 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, MMI, MPE, MWE	Yes	AURORA2 (purch.) AURORA3 (purch.), AURORA4 (WSJ0), CHIME-1, CHIME-2-I, CHIME-2-II,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 paper mail-list forum SVN	uncertain features diagonal uncertainty decoding Matlab conversion tools DNN Uncertainty Decoding	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	Yes	AURORA4 (WSJ0), CHIME-2	Weniger2014-REVERB Paper Code
Spraak	2008-* (1.1.374)	Yes	proprietary	Windows (limited), Linux, OSX	website paper mail-list forum SVN	Missing Data Techniques (MDT)	C, Python	No	Yes	Flexible preprocessing script language -- examples for MFCC, PLP	VTLN,CMN, MIDA, MDT Techniques, Parametric HistEq [1], Noise normalization [2]	GMM (Tied-Mix), Exemplar based [3], NN, CRF, ... (flexible using the preprocessing script) [4]	CMLLR, eigenvoices, GMM-weight based (NMF) [5] -- (all have Matlab dependencies); MAP	aligment, lattice rescoring, SCRF rescoring (using SCARF) [6], phone lattice rescoring [7]	Viterbi	Yes	AURORA4, [8]
Julius	1997-* (4.3.1)	Yes	propietary	Windows, Linux, OSX	website book book online mail-list forum CVS	htk2Julius grammar phoneme seg.	C	No	Yes	MFCC	VTLN,CMVN	GMM (Tied-Mix)		aligment, two-pass decoder	Baum-Welch	Yes (low latency)
RWTH	2001-* (0.6.1)	Yes	non-commercial	Windows, Linux, OSX	website paper wiki forum		C	BLAS, LAPACK, GPU (CUDA), OpenMP	Yes	MFCC, PLP, Gammatone, Tandem (MLP)	VTLN, CMVN, PCA, LDA	GMM (Tied covariance), DNN	MLLR, CMLLR, BIC	aligment, lattice rescoring, system fusion	Baum-Welch, MPE	Yes

Speaker identification and verification

Software	General attributes						Programming		Implemented techniques								Reproducible research
	release / update	actively developed	licence	platforms	links	extensions	language	hardware optimization	VAD	acoustic features	feature normalization	UBM	subspace projection	subspace normalization	scoring	diarization	robust recognition recipes	reproducible results
BECARS	2002-2005 (1.1.9)	No	CeCILL	Windows, Linux	download paper		C	No	No	MFCC	Gaussianization	GMM			MMI-weighted LLR	No
ALIZE	2005-*	Yes	LGPL	Windows, Linux, OSX	download mail-list linkedin paper		C++, Perl, Bash	No	Yes	MFCC, LFCC	CMVN	GMM	JFA, i-vector	whitening, length norm, LDA, WCCN	cosine, Mahalanobis, SVM, PLDA, Z/T norm	Yes
LIUM SpkDiarization	2009-2013	No	GPL	Windows, Linux, OSX	download paper	Python extension	Java	No	Yes	MFCC, LFCC	CMVN	GMM	i-vector		cosine, Mahalanobis	Yes
MSR Identity Toolbox	2013	No	proprietary	Windows, Linux, OSX	download paper		Matlab	No	Yes	MFCC	CMVN, Gaussianization	GMM	i-vector	whitening, length norm, LDA	PLDA	No
SPEAR	2014-*	Yes	GPL	Windows, Linux, OSX	download paper		Python	SGE grid	Yes	MFCC, LFCC	CMVN	GMM	ISV, JFA, i-vector	whitening, length norm, LDA, WCCN	PLDA, Z/T norm, score fusion	Yes

Speech enhancement and separation

Software	General attributes						Programming		Implemented techniques				Reproducible research
	release / update	actively developed	licence	platforms	links	extensions	language	hardware optimization	spatial model	spectral model	estimation algorithm	online separation	public recipes	reproducible results
BTK	2005-*	Yes	proprietary	Linux, OSX	download papers		C++, Python	BLAS	DS, SD, MVDR, MN beamforming; Zelinski, McCowan, Lefkimmiatis post-filters	none	GCC-PHAT localization	Yes
MESSL	2006-2009	No	proprietary	Windows, Linux, OSX	download paper		Matlab	No	IPD/ILD clustering	none	EM	No
BeamformIt	2006-2014 (3.51)	Yes	ICSI Open Source Speech Tools	Windows, Linux, OSX	download paper thesis		C++	No	weighted DS beamforming	none	GCC-PHAT localization	Yes	NIST RT06 (included), AMI
ManyEars	2007-2014 (1.1.2)	Yes	GPL	Windows, Linux, OSX	download paper		C	No	geometric ICA	Wiener post-filter (noise only)	CC-PHAT localization	No
HARK	2010-* (2.1.2)	Yes	non-commercial	Windows, Linux, OSX	download paper		C++	BLAS	DS, weighted DS, LCMV, GJ, max SNR beamforming; geometric ICA	Wiener post-filter (noise only)	MUSIC localization; MCRA noise estimation	Yes
FASST	2012-* (2.0)	Yes	QPL	Windows, Linux, OSX	download paper		C++, Matlab, Python	OpenMP	full-rank spatial covariance model	NMF, source-filter NMF, harmonic NMF, smooth NMF	EM and multiplicative updates	No

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.