Speaker Normalization And Pronunciation Variant Modeling: Helpful Methods For Improving Recognition Of Fast Speech (1999)
| Venue: | Proceedings of Eurospeech |
| Citations: | 3 - 1 self |
BibTeX
@INPROCEEDINGS{Pfau99speakernormalization,
author = {Thilo Pfau and Robert Faltlhauser and Günther Ruske},
title = {Speaker Normalization And Pronunciation Variant Modeling: Helpful Methods For Improving Recognition Of Fast Speech},
booktitle = {Proceedings of Eurospeech},
year = {1999},
pages = {299--302}
}
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Abstract
The presented paper addresses the problem of creating hidden Markov models for fast speech. The major issues discussed are robust parameter estimation and reducing within-model variations. Regarding the first issue, the use of the maximum a posteriori parameter estimation is discussed. To reduce within-model variations, a maximum likelihood based vocal tract length normalization procedure and a statistical approach to model pronunciation variants are applied. Experiments with a large vocabulary continuous speech recognition system were carried out on the German spontaneous scheduling task (Verbmobil) to prove the effectiveness of the investigated methods. The results show that a combination of pronunciation variant modeling and vocal tract length normalization is most effective. On fast speech, a relative improvement of 16.3% compared to the baseline models was achieved. Pronunciation variant modeling combined with the maximum a posteriori reestimation proved to be the...
