This paper addresses the problem of speech recognition in noise using speaker-dependent temporal constraints in the Viterbi algorithm in combination with speaker-independent HMM. It is shown that the speaker-dependent re-estimation of state duration parameters requires a low computational load and a small training database, and can lead to reductions in the error rate as high as 30% or 40% with clean signals and with signals corrupted by additive noise, without noise canceling methods. Moreover, the approach here covered could also be seen as a speaker adaptation method in which only temporal restrictions parameters are adapted.
Cite as: Yoma, N.B. (2000) Speaker dependent temporal constraints combined with speaker independent HMM for speech recognition in noise. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 3, 526-529
@inproceedings{yoma00_icslp,
author={Néstor Becerra Yoma},
title={{Speaker dependent temporal constraints combined with speaker independent HMM for speech recognition in noise}},
year=2000,
booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
pages={vol. 3, 526-529}
}