著者

Hattori Hiroaki Nakamura Satoshi Shikano Kiyohiro Sagayama Shigeki

出版者

一般社団法人電子情報通信学会

雑誌

IEICE transactions on information and systems (ISSN:09168532)

巻号頁・発行日

vol.76, no.2, pp.219-226, 1993-02-25

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This paper proposes a new speaker adaptation method using a speaker weighting technique for multiple reference speaker training of a hidden Markov model (HMM). The proposed method considers the similarities between an input speaker and multiple reference speakers, and use the similarities to control the influence of the reference speakers upon HMM. The evaluation experiments were carried out through the / b,d,g,m,n,N / phoneme recognition task using 8 speakers. Average recognition rates were 68.0%, 66.4%, and 65.6% respectively for three test sets which have different speech styles. These were .8%, 8.8%, and 10.5% higher than the rates of the spectrum mapping method, and also 1.6%, 6.7%, and 8.2% higher than the rates of the multiple reference speaker training, the supplemented HMM. The evaluation experiments clarified the effectiveness of the proposed method.