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

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概要

• 論文の詳細を見る

• 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 iteratively 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.

• 社団法人電子情報通信学会の論文
• 1995-06-25

著者

• Wu Chien-hsing

  Telecommunication Laboratories Ministry Of Communications Taiwan R.o.c

• Lin Chih-Heng

  Telecommunication Laboratories, Ministry of Communications, Taiwan R.O.C

• Chang Pao-Chung

  Telecommunication Laboratories, Ministry of Communications, Taiwan R.O.C

• Lin Chih-heng

  Telecommunication Laboratories Ministry Of Communications Taiwan R.o.c

• Chang P‐c

  Chunghwa Telecom Lab. Taoyuan Twn

関連論文

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

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