DocumentCode :
1499438
Title :
Cepstrum-based pitch detection using a new statistical V/UV classification algorithm
Author :
Ahmadi, Siavash ; Spanias, A.S.
Author_Institution :
Nokia Mobile Phones Inc., San Diego, CA
Volume :
7
Issue :
3
fYear :
1999
fDate :
5/1/1999 12:00:00 AM
Firstpage :
333
Lastpage :
338
Abstract :
An improved cepstrum-based voicing detection and pitch determination algorithm is presented. Voicing decisions are made using a multifeature voiced/unvoiced classification algorithm based on statistical analysis of cepstral peak, zero-crossing rate, and energy of short-time segments of the speech signal. Pitch frequency information is extracted by a modified cepstrum-based method and then carefully refined using pitch tracking, correction, and smoothing algorithms. Performance analysis on a large database indicates considerable improvement relative to the conventional cepstrum method. The proposed algorithm is also shown to be robust to additive noise
Keywords :
cepstral analysis; feature extraction; frequency estimation; signal classification; signal detection; smoothing methods; speech processing; statistical analysis; additive noise; cepstral peak; cepstrum-based pitch detection; large database; modified cepstrum-based method; multifeature voiced/unvoiced classification algorithm; objective error measures; performance analysis; pitch determination algorithm; pitch frequency information; pitch tracking; short-time segments energy; smoothing algorithms; speech signal; statistical V/UV classification algorithm; statistical analysis; voicing detection; zero-crossing rate; Cepstral analysis; Cepstrum; Classification algorithms; Data mining; Databases; Frequency; Performance analysis; Smoothing methods; Speech analysis; Statistical analysis;
fLanguage :
English
Journal_Title :
Speech and Audio Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-6676
Type :
jour
DOI :
10.1109/89.759042
Filename :
759042
Link To Document :
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