DocumentCode :
2461701
Title :
Enhancement Pattern Analysis Technique for Voiced/Unvoiced Classification
Author :
Pattanaburi, Kreangsak ; Njit, Jak Krit Onshau ; Chat, Jak Kree Srinon
Author_Institution :
Electron. & Telecommun. Eng. Dept., Rajamangala Univ. of Technol., Thanyaburi, Thailand
fYear :
2012
fDate :
4-6 June 2012
Firstpage :
389
Lastpage :
392
Abstract :
Requirement to deciding whether a given frame of a speech waveform should be classified as voiced speech or unvoiced speech arises in many speech analysis systems. Several approaches have been described in the literature for making this decision. In this article presents four enhancement pattern analysis techniques to classify voiced and unvoiced based on the linear predictive coefficients. Those techniques are also compared the performance with the prosodic technique. Ten minutes of speech signal are collected to be input speech. The results show that the 4th technique provides the best performance of the quality of V/UV classification at 89.29% with 19,356 voiced frame. This technique can apply to vector quantization technique for speech compression and speech recognition which usually uses the LP coefficients as the speech feature.
Keywords :
signal classification; speech coding; speech recognition; vector quantisation; decision making; enhancement pattern analysis technique; linear predictive coefficient; speech analysis system; speech compression; speech recognition; speech waveform frame classification; unvoiced classification; vector quantization technique; voiced classification; Educational institutions; Pattern analysis; Speech; Speech coding; Speech processing; Speech recognition; Standards; linear predictive coefficients; pattern analysis; voiced/unvoice classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer, Consumer and Control (IS3C), 2012 International Symposium on
Conference_Location :
Taichung
Print_ISBN :
978-1-4673-0767-3
Type :
conf
DOI :
10.1109/IS3C.2012.105
Filename :
6228328
Link To Document :
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