A New Pitch Detection Algorithm Based on RCAF

Author

Yue, Wang ; Zhihong, Qian ; Ying, Zhang

Author_Institution

Coll. of Commun. Eng., Jilin Univ., Changchun, China

Volume

6

fYear

2009

fDate

March 31 2009-April 2 2009

Firstpage

126

Lastpage

130

Abstract

A new pitch detection of noisy speech signal for lower SNR is proposed in this paper. This method is a novel algorithm of Reverse CAMDF Autocorrelation Function (RCAF) pitch extraction from noisy speech based on searching and tentative smooth measure. The algorithm can estimate noise during speech presence, which employs the method of expanded spectral subtraction based on the noise compensation structure. A number of experiments show that by the RCAF method, higher efficiency and better detection accuracy can be obtained while the SNR is equal to -10 dB. However, such performance cannot be achieved by traditional methods, AMDF, CAMDF and AWAC with the same SNR.

Keywords

correlation methods; noise; search problems; smoothing methods; spectral analysis; speech processing; circular average magnitude difference function; noise compensation structure; noisy speech signal; pitch detection algorithm; pitch extraction; reverse CAMDF autocorrelation function; signal-to-noise ratio; smooth measure; spectral subtraction; Autocorrelation; Detection algorithms; Iterative algorithms; Signal processing algorithms; Signal to noise ratio; Speech enhancement; Speech processing; Speech synthesis; Wiener filter; Working environment noise; Expanded Spectral Subtraction; Pitch detection; Reverse CAMDF Autocorrelation Function;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Information Engineering, 2009 WRI World Congress on

Conference_Location

Los Angeles, CA

Print_ISBN

978-0-7695-3507-4

Type

conf

DOI

10.1109/CSIE.2009.382

Filename

5170674