Comparing maximum a posteriori vector quantization and Gaussian mixture models in speaker verification

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2009, Pages 4229-4232

  Kinnunen, Tomi ^a   Saastamoinen, Juhani ^a   Hautamäki, Ville ^a   Vinni, Mikko ^a   Fränti, Pasi ^a  

^a UNIVERSITY OF EASTERN FINLAND   (Finland)

Author keywords

Gaussian mixture model (GMM); Map training; MFCCs; Speaker verification; Vector quantization (VQ)

Indexed keywords

DISCRIMINATIVE CLASSIFIERS; GAUSSIAN MIXTURE MODEL; GAUSSIAN MIXTURE MODEL (GMM); GAUSSIAN MIXTURE MODEL - UNIVERSAL BACKGROUND MODEL; MAXIMUM A POSTERIORI; MFCCS; MODEL ORDER; PARAMETER SETTING; REFERENCE POINTS; SHORT SEGMENTS; SIMPLIFIED MODELS; SPEAKER VERIFICATION; TRAINING DATA;

ACOUSTICS; BLIND SOURCE SEPARATION; CLASSIFIERS; COMMUNICATION CHANNELS (INFORMATION THEORY); LEARNING SYSTEMS; MAGNETOSTRICTIVE DEVICES; MAXIMUM LIKELIHOOD; MIXTURES; OBJECT RECOGNITION; SIGNAL PROCESSING; SPEECH RECOGNITION; VECTORS;

VECTOR QUANTIZATION;

EID: 70349226835     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2009.4960562     Document Type: Conference Paper

References (10)

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