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Class-based Gaussian selection for efficient decoding in PTM HMMs

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3 Author(s)
Son, J. ; Sch. of Electron. & Electr. Eng., Kyungpook Nat. Univ., South Korea ; Jung, S. ; Bae, K.

A new Gaussian selection (GS) method is presented for fast decoding in phonetic tied-mixture (PTM) hidden Markov models (HMMs). For efficient likelihood computation, a constraint is imposed on the context-dependent weights as well as the number of Gaussians. Experimental results demonstrate the superiority of the proposed method over conventional GS methods.

Published in:

Electronics Letters  (Volume:40 ,  Issue: 2 )