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Using multi-level segmentation coefficients to improve HMM speech recognition

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1 Author(s)
K. Hubener ; Dept. of Comput. Sci., Hamburg Univ., Germany

This paper presents a new kind of acoustic features for HMM speech recognition. These features try to capture phone-specific segmentation information using multiple temporal resolutions. Experiments show that word accuracy can be improved by 7% when combining these features with traditional mel-cepstral coefficients in a speaker-independent word recogniser. This improvement is mostly due to a reduced number of insertion and deletion errors

Published in:

Spoken Language, 1996. ICSLP 96. Proceedings., Fourth International Conference on  (Volume:1 )

Date of Conference:

3-6 Oct 1996