Title :
Weighted autocorrelation for pitch extraction of noisy speech
Author :
Shimamura, Tetsuya ; Kobayashi, Hajime
Author_Institution :
Dept. of Inf. & Comput. Sci., Saitama Univ., Urawa, Japan
fDate :
10/1/2001 12:00:00 AM
Abstract :
In this paper, we propose a modified version of the autocorrelation pitch extraction method well known to be robust against noise. Utilizing that the average magnitude difference function (AMDF) has similar characteristics with the autocorrelation function, the autocorrelation function is weighted by the reciprocal of the AMDF. By simulation experiments, it is shown that the proposed pitch extraction method is useful in noisy environments
Keywords :
acoustic correlation; acoustic noise; frequency estimation; speech processing; AMDF; autocorrelation function; average magnitude difference function; noisy environments; noisy speech; pitch extraction; weighted autocorrelation; Additive white noise; Autocorrelation; Data mining; Frequency; Noise robustness; Oral communication; Speech enhancement; Speech processing; Testing; Working environment noise;
Journal_Title :
Speech and Audio Processing, IEEE Transactions on
