Modeling speech signals in the time–frequency domain using GARCH-Reference-Cited by-同舟云学术

Modeling speech signals in the time–frequency domain using GARCH

Published:2004-12 Issue:12 Volume:84 Page:2453-2459
ISSN:0165-1684
Container-title:Signal Processing
language:en
Short-container-title:Signal Processing

Author:

Cohen Israel

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software,Control and Systems Engineering

Reference12 articles.

1. Generalized autoregressive conditional heteroskedasticity;Bollerslev;J. Econometrics,1986

2. ARCH modeling in finance;Bollerslev;J. Econometrics,1992

3. Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressor;Cappé;IEEE Trans. Acoust. Speech Signal Process.,1994

4. I. Cohen, Speech spectral modeling and enhancement based on autoregressive conditional heteroscedasticity model, also Technical Report, EE PUB 1425, Technion, Israel Institute of Technology, Haifa, Israel, April 2004, submitted for publication.

5. Speech enhancement for non-stationary noise environments;Cohen;Signal Process.,2001

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