DocumentCode
2147192
Title
Linear predictive analysis of noisy speech
Author
Zhao, Qifang ; Shimamura, Tetsuya ; Suzuki, Jouji
Author_Institution
Dept. of Inf. & Comput. Sci., Saitama Univ., Urawa, Japan
Volume
2
fYear
1997
fDate
20-22 Aug 1997
Firstpage
585
Abstract
New methods are proposed to improve the robustness of the linear predictive (LPC) analysis of speech to noise. These methods are developed based on the concept of noise compensation. By subtracting the noise power from the autocorrelation function of speech iteratively, the proposed methods achieve success in both reducing the bias of the LPC coefficients and guaranteeing the stability of the LPC inverse filter
Keywords
acoustic noise; cepstral analysis; compensation; correlation methods; filtering theory; iterative methods; parameter estimation; prediction theory; speech processing; LPC coefficients; autocorrelation function; cepstrum distance; inverse filter; iterative method; linear predictive analysis; noise compensation; noise power; noisy speech; robustness; stability; Acoustic reflection; Autocorrelation; Equations; Linear predictive coding; Noise reduction; Noise robustness; Speech analysis; Speech enhancement; Stability; White noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Communications, Computers and Signal Processing, 1997. 10 Years PACRIM 1987-1997 - Networking the Pacific Rim. 1997 IEEE Pacific Rim Conference on
Conference_Location
Victoria, BC
Print_ISBN
0-7803-3905-3
Type
conf
DOI
10.1109/PACRIM.1997.620331
Filename
620331
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