Two dissimilarity measures for HMMs and their application in phoneme model clustering

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

Volumn 1, Issue , 2002, Pages 933-936

  Vihola, Matti ^a   Harju, Mikko ^b   Salmela, Petri ^b   Suontausta, Janne ^c   Savela, Janne ^d  

^a TAMPERE UNIVERSITY OF TECHNOLOGY   (Finland)

^b Institute of Digital and Computer Systems   (Finland)

^c NOKIA RESEARCH CENTER   (United States)

^d UNIVERSITY OF TURKU   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

GAUSSIAN OBSERVATION DENSITIES; HIDDEN MARKOV MODEL; KULLBACK-LEIBLER DIVERGENCE;

APPROXIMATION THEORY; COMPUTER SIMULATION; MATHEMATICAL MODELS; MONTE CARLO METHODS; PROBABILITY DENSITY FUNCTION; PROBABILITY DISTRIBUTIONS; SPEECH ANALYSIS; SPEECH RECOGNITION; TOPOLOGY;

MARKOV PROCESSES;

EID: 0036289980     PISSN: 15206149     EISSN: None     Source Type: Journal    
DOI: 10.1109/ICASSP.2002.5743946     Document Type: Article

References (9)

1. A probabilistic distance measure for hidden Markov models
2. Calculation of distance measures between hidden Markov models
3. Multilingual phone models for vocabulary-independent speech recognition tasks
4. SpeechDat: Definition of corpus, scripts and standards for fixed networks
5. Comparing parameter tying techniques for multilingual acoustic modelling
6. Cepstral domain segmental feature normalization for noise robust speech recognition