Third International Conference on Spoken Language Processing (ICSLP 94)

Yokohama, Japan
September 18-22, 1994

Speaker Adaptation Based on Fuzzy Vector Quantization

Jun'ichi Nakahashi, Eiichi Tsuboka

Central Research Laboratories, Matsushita Electric Industrial Co.,Ltd., Kyoto, Japan

In this paper, we propose the following four speaker adaptation methods based on Fuzzy Vector Quantization (FVQ),

All these methods adapt the reference codebook using adaptation vector, estimated for a certain criterion. The experiments show that all these methods have better performance in comparison with speaker-independent isolated word recognition, when applied to FVQ/HMM. In particular unsupervised speaker adaptation shows that the word recognition rate for "outlier" speakers has been improved from 84.2 % to 88.9 % using 5 adaptation words.

Full Paper

Bibliographic reference.  Nakahashi, Jun'ichi / Tsuboka, Eiichi (1994): "Speaker adaptation based on fuzzy vector quantization", In ICSLP-1994, 467-470.