Comparison of wavelet- and FFT-based single-channel speech signal noise reduction techniques

Ningping Fan; Radu V. Balan; Justinian Rosca

doi:10.1117/12.574050

1 November 2004 Comparison of wavelet- and FFT-based single-channel speech signal noise reduction techniques

Ningping Fan, Radu V. Balan, Justinian Rosca

Proceedings Volume 5607, Wavelet Applications in Industrial Processing II; (2004) https://doi.org/10.1117/12.574050
Event: Optics East, 2004, Philadelphia, Pennsylvania, United States

Abstract

This paper compares wavelet and short time Fourier transform based techniques for single channel speech signal noise reduction. Despite success of wavelet denoising of images, it has not yet been widely used for removal of noise in speech signals. We explored how to extend this technique to speech denoising, and discovered some problems in this endeavor. Experimental comparison with large amount test data has been performed. Our results have shown that although the Fourier domain methods still has the superiority, wavelet based alternatives can be very close, and enormous different configurations can still be tried out for possible better solutions.

Citation Download Citation

Ningping Fan, Radu V. Balan, and Justinian Rosca "Comparison of wavelet- and FFT-based single-channel speech signal noise reduction techniques", Proc. SPIE 5607, Wavelet Applications in Industrial Processing II, (1 November 2004); https://doi.org/10.1117/12.574050

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available