Automatic Speech Segmentation Based on HMM
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Date
2007-06
Authors
Kroul, Martin
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Společnost pro radioelektronické inženýrství
Abstract
This contribution deals with the problem of automatic phoneme segmentation using HMMs. Automatization of speech segmentation task is important for applications, where large amount of data is needed to process, so manual segmentation is out of the question. In this paper we focus on automatic segmentation of recordings, which will be used for triphone synthesis unit database creation. For speech synthesis, the speech unit quality is a crucial aspect, so the maximal accuracy in segmentation is needed here. In this work, different kinds of HMMs with various parameters have been trained and their usefulness for automatic segmentation is discussed. At the end of this work, some segmentation accuracy tests of all models are presented.
Description
Citation
Radioengineering. 2007, vol. 16, č. 2, s. 56-61. ISSN 1210-2512
http://www.radioeng.cz/fulltexts/2007/07_02_56_61.pdf
http://www.radioeng.cz/fulltexts/2007/07_02_56_61.pdf
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en