DocumentCode
3205496
Title
Automatic speech segmentation for Chinese speech database based on HMM
Author
Tao, Jianhua ; Hain, Horst-Udo
Author_Institution
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Volume
1
fYear
2002
fDate
28-31 Oct. 2002
Firstpage
481
Abstract
The paper offers an optimized method for speech segmentation of a Mandarin speech database by using a hidden Markov model (HMM). The method takes the syllable boundaries into account. Testing shows that the accuracy of results is improved to 95% from 88% compared to the normal method. In particular, most of the boundaries between two vowels can also be well detected with the new method. The paper also analyzes the influence of the amount of HMM states and the amount of the training corpus.
Keywords
hidden Markov models; optimisation; speech processing; Chinese speech database; HMM states; Mandarin speech database; automatic speech segmentation; hidden Markov model; optimized method; syllable boundaries; training corpus; Computer science; Databases; Hidden Markov models; Labeling; Optimization methods; Paper technology; Personal digital assistants; Speech processing; Speech synthesis; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON '02. Proceedings. 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering
Print_ISBN
0-7803-7490-8
Type
conf
DOI
10.1109/TENCON.2002.1181318
Filename
1181318
Link To Document