This paper describes a high speed algorithm for a speech recognizer based on speaker cluster HMM. The speaker cluster HMM, which enables to deal with variety among speakers, have been reported to show good performance. However, the computation amount grows in proportion to the number of clusters, when the speaker cluster HMM is used in speaker independent recognition, where the recognition processes must be run in parallel using every speaker cluster HMM. To reduce the computation, we introduced the multi-pass search for searching on the broad space covering lexical and speaker variation. Furthermore, the output probability recalculation is introduced to reduce the state output probability computation. We had some experiments on 1000 word speaker independent continuous telephone speech recognition. The result in the case where 7 speaker clusters are used shows about 30% of computation reduction.
Cite as: Yamada, M., Komori, Y., Kosaka, T., Yamamoto, H. (1997) Fast algorithm for speech recognition using speaker cluster HMM. Proc. 5th European Conference on Speech Communication and Technology (Eurospeech 1997), 2043-2046, doi: 10.21437/Eurospeech.1997-541
@inproceedings{yamada97_eurospeech,
author={Masayuki Yamada and Yasuhiro Komori and Tetsuo Kosaka and Hiroki Yamamoto},
title={{Fast algorithm for speech recognition using speaker cluster HMM}},
year=1997,
booktitle={Proc. 5th European Conference on Speech Communication and Technology (Eurospeech 1997)},
pages={2043--2046},
doi={10.21437/Eurospeech.1997-541}
}