Improved spectral subtraction utilizing iterative processing

Abstract

In this paper, the authors propose a new noise suppression technique that executes iterative processing and sets parameters that are suited for that processing in the spectral subtraction method, which is a noise reduction technique for noise-added speech. Iterative processing is a technique in which speech enhancement processing is executed by considering the estimated speech that is obtained when noise reduction processing is executed once as the input signal again so that a reduction of the residual noise is anticipated. A further reduction of residual noise for which speech degradation is controlled can be achieved by adjusting the parameters for each iteration. The authors also simultaneously propose a technique for maintaining the real-time nature of spectral subtraction when the proposed technique is executed. They use actual speech to which white noise, automobile noise, and crowd babble noise is added to compare the characteristics of the two proposed methods with the conventional spectral subtraction method and its improvements. The authors verified according to objective and subjective evaluations that each proposed technique showed superior results in all noisy environments. © 2006 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 90(4): 39 –51, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20242