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Classification of transition sounds with application to automatic speech recognition

Zeev Litichever, Dan Chazan
2001 7th European Conference on Speech Communication and Technology (Eurospeech 2001)   unpublished

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This paper addresses the problem of classification of speech transition sounds. A number of non parametric classifiers are compared, and it is shown that some non-parametric classifiers have considerable advantages over traditional hidden Markov models. Among the non-parametric classifiers, support vector machines were found the most suitable and the easiest to tune. Some of the reasons for the superiority of non-parametric classifiers will be discussed. The algorithm was tested on the voiced
more » ... op consonant phones extracted from the TIMIT corpus and resulted in very low error rates.
doi:10.21437/eurospeech.2001-422 fatcat:nxgh6hslhbcebbyuqxhiaujlay
Citation

Zeev Litichever, Dan Chazan. "Classification of transition sounds with application to automatic speech recognition." 7th European Conference on Speech Communication and Technology (Eurospeech 2001) (2001)