The Phoneme Automatic Segmentation Algorithms Study of Tibetan Lhasa Words Continuous Speech Stream

DOI

10.2991/icsem.2013.114How to use a DOI?

Keywords

Tibetan, Corpus, Phoneme automatic segmentation

Abstract

In this paper, we adopt two methods to voice phoneme segmentation when building Tibetan corpus: One is the traditional artificial segmentation method, one is the automatic segmentation method based on the Mono prime HMM model. And experiments are performed to analyze the accuracy of both methods of segmentations. The results showed: Automatic segmentation method based tone prime HMM model helps to shorten the cycle of building Tibetan corpus, especially in building a large corpus segmentation and labeling a lot of time and manpower cost savings, and have greatly improved the accuracy and consistency of speech corpus annotation information.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jin-xi Zhang
AU  - Hong-zhi Yu
AU  - Ning Ma
AU  - Zhao-yao LI
PY  - 2013/04
DA  - 2013/04
TI  - The Phoneme Automatic Segmentation Algorithms Study of Tibetan Lhasa Words Continuous Speech Stream
BT  - Proceedings of the 2nd International Conference On Systems Engineering and Modeling (ICSEM 2013)
PB  - Atlantis Press
SP  - 578
EP  - 581
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.114
DO  - 10.2991/icsem.2013.114
ID  - Zhang2013/04
ER  -