HMM-based reconstruction of unreliable spectrographic data for noise robust speech recognition

IEEE Transactions on Audio, Speech and Language Processing

Volumn 18, Issue 6, 2010, Pages 1612-1623

  Borgstrom, Bengt J ^a   Alwan, Abeer ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Hidden Markov models (HMMs); mask estimation; missing features (MFs); noise robust speech recognition; spectral reconstruction

Indexed keywords

BASELINE SYSTEMS; DECODING METHODS; DOWNSAMPLING; ESTIMATION METHODS; LOWER RESOLUTION; MEL-FREQUENCY CEPSTRAL COEFFICIENTS; MEMORY REQUIREMENTS; MINIMUM MEAN-SQUARE ERROR; MISSING FEATURES (MFS); MODEL PARAMETERS; NOISE ROBUST SPEECH RECOGNITION; PERFORMANCE BOUNDS; QUANTIZERS; REALISTIC SCENARIO; RECONSTRUCTION ALGORITHMS; RECONSTRUCTION METHOD; ROBUST RECOGNITION; SPECTRAL MAGNITUDES; SPECTRAL RECONSTRUCTION; SPECTROGRAPHIC DATA; SPEECH DATA; STRUCTURED MAPPINGS;

COMPUTATIONAL EFFICIENCY; ESTIMATION; HIDDEN MARKOV MODELS; NATURAL LANGUAGE PROCESSING SYSTEMS; REPAIR; STOCHASTIC MODELS;

SPEECH RECOGNITION;

EID: 77955777921     PISSN: 15587916     EISSN: None     Source Type: Journal    
DOI: 10.1109/TASL.2009.2038811     Document Type: Article

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