DocumentCode
2838295
Title
A novel two-step SVM classifier for voiced/unvoiced/silence classification of speech
Author
Qi, Fengyan ; Bao, Changchun ; Liu, Yan
Author_Institution
Speech & Audio Signal Process. Lab, Beijing Univ. of Technol., China
fYear
2004
fDate
15-18 Dec. 2004
Firstpage
77
Lastpage
80
Abstract
In this paper, a novel method for voiced/unvoiced/silence of speech classification using the support vector machine (SVM) is proposed. This classifier can correctly classify speech frames into voiced frame, unvoiced frame and silence frame. The comparison of experimental results show that the proposed method outperforms other traditional methods. The performance of SVM for different kernel functions in the experiment was analyzed and discussed as well.
Keywords
signal classification; speech processing; speech recognition; support vector machines; kernel functions; silence frame; speech classification; speech frames; support vector machine; two-step SVM classifier; unvoiced frame; voiced frame; Classification algorithms; Kernel; Machine learning algorithms; Neural networks; Pattern classification; Speech processing; Speech recognition; Statistical distributions; Support vector machine classification; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Chinese Spoken Language Processing, 2004 International Symposium on
Print_ISBN
0-7803-8678-7
Type
conf
DOI
10.1109/CHINSL.2004.1409590
Filename
1409590
Link To Document