A Study on Speaker Adaptation for Mandarin Syllable Recognition with Minimum Error Discriminative Training

Chih-Heng LIN  Chien-Hsing WU  Pao-Chung CHANG  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E78-D   No.6   pp.712-718
Publication Date: 1995/06/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Spoken Language Processing)
Category: 
Keyword: 
speaker-adaptation,  discriminative training,  Mandarin syllable recognition,  confusion set,  

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Summary: 
This paper investigates a different method of speaker adaptation for Mandarin syllable recognition. Based on the minimum classification error (MCE) criterion, we use the generalized probabilistic decent (GPD) algorithm to adjust interatively the parameters of the hidden Markov models (HMM). The experiments on the multi-speaker Mandarin syllable database of Telecommunication Laboratories (T.L.) yield the following results: 1) Efficient speaker adaptation can be achieved through discriminative training using the MCE criterion and the GPD algorithm. 2) The computations required can be reduced through the use of the confusion sets in Mandarin base syllables. 3) For the discriminative training, the adjustment on the mean values of the Gaussian mixtures has the most prominent effect on speaker adaptation. 4) The discriminative training approach can be used to enhance the speaker adaptation capability of the maximum a posteriori (MAP) approach.