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2001 7th European Conference on Speech Communication and Technology (Eurospeech 2001)   unpublished
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