DocumentCode :
3086958
Title :
Speech Recognition Based on Support Vector Machine and Error Correcting Output Codes
Author :
Liu Xiao-feng ; Zhang Xue-ying ; Ji-Kang, Duan
Author_Institution :
Dept. of Math., Taiyuan Univ. of Technol., Taiyuan, China
fYear :
2010
fDate :
17-19 Sept. 2010
Firstpage :
336
Lastpage :
339
Abstract :
A method is proposed based on application of Error Correcting Output Codes Support Vector Machine (ECOC-SVM) in order to get better results of speech recognition. Some uncorrelated SVMs are constructed based on ECOC matrix codes to improve the integrated performance of fault tolerance of classification model. This paper gives four commonly-used encodings of ECOC. By comparing the results with that of speech recognition based on HMM, the experiments indicate that the ECOC method is more suitable for speech recognition, among which the predicting accuracy of one-versus-one is the highest of all.
Keywords :
error correction codes; hidden Markov models; speech recognition; support vector machines; HMM; SVM; error correcting output codes; hidden Markov models; speech recognition; support vector machine; Accuracy; Encoding; Hidden Markov models; Speech; Speech recognition; Support vector machines; Training; Error Correcting Output Codes; Speech Recognition; Support Vector Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pervasive Computing Signal Processing and Applications (PCSPA), 2010 First International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-8043-2
Electronic_ISBN :
978-0-7695-4180-8
Type :
conf
DOI :
10.1109/PCSPA.2010.88
Filename :
5635824
Link To Document :
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