Finite mixture spectrogram modeling for multipitch tracking using a factorial hidden Markov model

Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

Volumn , Issue , 2009, Pages 1079-1082

  Wohlmayr, Michael ^a   Pernkopf, Franz ^a  

^a GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

Factorial hidden Markov model; Minimum description length; Multipitch tracking; Pitch estimation

Indexed keywords

CORRELOGRAM FEATURE; CORRELOGRAMS; FEATURE MODELING; FINITE MIXTURES; GAUSSIAN COMPONENTS; GAUSSIAN MIXTURE MODELS; MINIMUM DESCRIPTION LENGTH; MODEL SELECTION CRITERIA; MULTIPITCH TRACKING; PITCH ESTIMATION; PITCH-TRACKING; SPECTROGRAMS; SPEECH UTTERANCE; TIMIT DATABASE; WHITE GAUSSIAN NOISE;

ACOUSTIC VARIABLES MEASUREMENT; COMPUTER VISION; GAUSSIAN NOISE (ELECTRONIC); HIDDEN MARKOV MODELS; OBJECT RECOGNITION; SPECTROGRAPHS; SPEECH COMMUNICATION;

CONTINUOUS SPEECH RECOGNITION;

EID: 70450177302     PISSN: None     EISSN: 19909772     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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