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A New HMnet Construction Algorithm Requiring No Contextual Factors

Motoyuki SUZUKI, Shozo MAKINO, Akinori ITO, Hirotomo ASO, Hiroshi SHIMODAIRA

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Summary :

Many methods have been proposed for constructing context-dependent phoneme models using Hidden Markov Models (HMMs) to improve performance. These conventional methods require previously defined contextual factors. If these factors are deficient, the method exhibit poor recognition performance. In this paper, we propose a new construction algorithm for HMnet which does not require pre-defined contextual factors. Experiments demonstrated that the new algorithm could construct the HMnet even for the case that the Successive State Splitting (SSS) algorithm could not. The new algorithm produced better phoneme recognition characteristics than the SSS algorithm.

Publication
IEICE TRANSACTIONS on Information Vol.E78-D No.6 pp.662-668
Publication Date
1995/06/25
Publicized
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Type of Manuscript
Special Section PAPER (Special Issue on Spoken Language Processing)
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