Reducing correlated noise in digital hearing aids

Abstract

The intelligibility of speech in communication systems is generally reduced by interfering noise. This interference, which can take the form of environmental noise, reverberation, competing speech, or electronic channel noise, reduces intelligibility by masking the signal of interest. The reduction in intelligibility is particularly troublesome for listeners with hearing impairments, who have greater difficulty understanding speech in the presence of noise than do normal-hearing listeners. Numerous digital signal processing (DSP)-based speech enhancement systems have been proposed to improve intelligibility in the presence of noise. Several of these systems have difficulty distinguishing between noise and consonants, and consequently attenuate both. Other methods, which use imprecise estimates of the noise, create audible artifacts that further mask consonants. The objective of the present study is to develop a new noise-reduction method that can reduce additive noise without impairing intelligibility. The new method could be used to improve intelligibility in a wide variety of applications, with special attention given to digital hearing aids and other portable communication systems (e.g., cellular telephones). Here, the authors present a new wavelet-based method for reducing correlated noise in noisy speech signals. The authors provide background information on the intelligibility problem and on previous attempts to address it. A theoretical framework is then proposed for reduction of correlated noise, along with some preliminary experimental results.