Software

This page provides software grouped by application.

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	robust ASR training 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, FE 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		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 (using OpenFST)	Baum-Welch, MMI (boosted), MC, feature-based	Yes	AURORA4 (WSJ0), CHIME-2	Weniger2014-REVERB Paper Code
Spraak	2008-* (1.1.374)	Yes	proprietary2	Windows (limited), Linux, OSX	website paper mail-list 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]

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• 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

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