DocumentCode :
3558776
Title :
Epoch Extraction From Speech Signals
Author :
Murty, K. Sri Rama ; Yegnanarayana, B.
Author_Institution :
Dept. of Comput. Sci. & Eng., Indian Inst. of Technol., Chennai
Volume :
16
Issue :
8
fYear :
2008
Firstpage :
1602
Lastpage :
1613
Abstract :
Epoch is the instant of significant excitation of the vocal-tract system during production of speech. For most voiced speech, the most significant excitation takes place around the instant of glottal closure. Extraction of epochs from speech is a challenging task due to time-varying characteristics of the source and the system. Most epoch extraction methods attempt to remove the characteristics of the vocal-tract system, in order to emphasize the excitation characteristics in the residual. The performance of such methods depends critically on our ability to model the system. In this paper, we propose a method for epoch extraction which does not depend critically on characteristics of the time-varying vocal-tract system. The method exploits the nature of impulse-like excitation. The proposed zero resonance frequency filter output brings out the epoch locations with high accuracy and reliability. The performance of the method is demonstrated using CMU-Arctic database using the epoch information from the electroglottograph as reference. The proposed method performs significantly better than the other methods currently available for epoch extraction. The interesting part of the results is that the epoch extraction by the proposed method seems to be robust against degradations like white noise, babble, high-frequency channel, and vehicle noise.
Keywords :
feature extraction; speech processing; electroglottograph; epoch extraction; reliability; speech signals; vocal-tract system; Data mining; Databases; Degradation; Filters; Noise robustness; Production systems; Resonance; Resonant frequency; Speech; Time varying systems; Epoch extraction; Hilbert envelope; glottal closure instant; group-delay; instantaneous frequency;
fLanguage :
English
Journal_Title :
Audio, Speech, and Language Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1558-7916
Type :
jour
DOI :
10.1109/TASL.2008.2004526
Filename :
4648930
Link To Document :
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