DocumentCode :
336795
Title :
A C/V segmentation algorithm for Mandarin speech signal based on wavelet transforms
Author :
Wang, Jhing-Fa ; Chen, Shi-Huang
Author_Institution :
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Volume :
1
fYear :
1999
fDate :
15-19 Mar 1999
Firstpage :
417
Abstract :
This paper proposes a new consonant/vowel (C/V) segmentation algorithm for Mandarin speech signal. Since the Mandarin phoneme structure is a combination of a consonant (may be null) followed by a vowel, the C/V segmentation is an important part in the Mandarin speech recognition system. Based on the wavelet transform, the proposed method can directly search for the C/V segmentation point by using a product function and energy profile. The product function is generated from the appropriate wavelet and scaling coefficients of the input speech signal, and it can be applied to indicate the C/V segmentation point. With this product function and the additional verification of the energy profile, the C/V segmentation can be accurately pointed out with a low computation complexity. Experiments are provided that demonstrate the superior performance of the proposed algorithm. An overall accuracy rate of 97.2% is achieved. This algorithm is suitable for Mandarin speech recognition task
Keywords :
computational complexity; natural languages; speech processing; speech recognition; wavelet transforms; C/V segmentation algorithm; Mandarin phoneme structure; Mandarin speech recognition system; Mandarin speech signal; accuracy rate; consonant/vowel segmentation algorithm; energy profile; input speech signal; low computation complexity; performance; product function; scaling coefficients; wavelet coefficients; wavelet transforms; Constitution; Decoding; Degradation; Hidden Markov models; Natural languages; Neural networks; Signal generators; Speech recognition; Vocabulary; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on
Conference_Location :
Phoenix, AZ
ISSN :
1520-6149
Print_ISBN :
0-7803-5041-3
Type :
conf
DOI :
10.1109/ICASSP.1999.758151
Filename :
758151
Link To Document :
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