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MATĚJKA, P., SCHWARZ, P., KARAFIÁT, M., ČERNOCKÝ, J.
Original Title
Some like it Gaussian ...
Type
conference paper
Language
English
Original Abstract
In Hidden Markov models, speech features are modeled by Gaussian distributions. In this paper, we propose to gaussianize the features to better fit to this modeling. A distribution of the data is estimated and a transform function is derived. We have tested two methods of the transform estimation (global and speaker based). The results are reported on recognition of isolated Czech words (SpeechDat-E) with CI and CD models and on medium vocabulary continuous speech recognition task (SPINE). Gaussianized data provided in all three cases results superior to standard MFC coefficients proving, that the gaussianization is a cheap way to increase the recognition accuracy.
Key words in English
speech,speech recognition,gaussianization
Authors
RIV year
2002
Released
8. 9. 2002
Location
Brno 2002
ISBN
3-540-44129-8
Book
Proceedings of the conference TSD'2002
Edition number
1
Pages from
321
Pages to
324
Pages count
4
BibTex
@inproceedings{BUT4282, author="Pavel {Matějka} and Petr {Schwarz} and Martin {Karafiát} and Jan {Černocký}", title="Some like it Gaussian ...", booktitle="Proceedings of the conference TSD'2002", year="2002", number="1", pages="4", address="Brno 2002", isbn="3-540-44129-8" }