Evaluation on unsupervised speaker adaptation based on sufficient HMM statictics of selected speakers
| Autor: | Shinichi, Yoshizawa, Akira, Baba, Kanako, Matsunami, Yuichiro, Mera, Miichi, Yamada, Akinobu, Lee, Kiyohiro, Shikano |
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| Rok vydání: | 2001 |
| Zdroj: | 7th European Conference on Speech Communication and Technology (Eurospeech 2001). |
| DOI: | 10.21437/eurospeech.2001-317 |
| Popis: | This paper describes an efficient method of unsupervised speaker adaptation. This method is based on (1) selecting a subset of speakers who are acoustically close to a test speaker, and (2) calculating adapted model parameters according to the previously stored sufficient statistics of the selected speakers' data. In this method, only a few unsupervised test speaker's data are necessary for the adaptation. Also, by using the sufficient HMM statistics of the selected speakers' data, a quick adaptation can be done. Compared with a pre-clustering method, the proposed method can obtain a more optimal cluster because the clustering result is determined according to test speaker's data on-line. Experimental results show that the proposed method attains better improvement than MLLR from the speaker-independent model. The proposed method is evaluated in details and discussed. EUROSPEECH2001: the 7th European Conference on Speech Communication and Technology, September 3-7, 2001, Aalborg, Denmark. |
| Databáze: | OpenAIRE |
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