An evaluation of adaptive noise cancellation as a technique for enhancing the intelligibility of noise-corrupted speech for the hearing impaired

The speech-to-noise ratio required under noisy conditions so that intelligibility is comparable to that in quiet is significantly higher for a hearing-impaired individual than a normal-hearing person. In this research a simple, efficient, real-time implementation of a single-input speechenhancement scheme, designed to increase the intelligibility of speech corrupted by additive noise using adaptive noise cancellation (ANC) techniques was evaluated with speech-discrimination tests using hearing-impaired subjects. Although many single-input speech-enhancement schemes have been shown to provide insignificant gains for the normal-hearing person, this work found that a hearing-impaired person’s ability to understand the speech processed using ANC can improve noticeably, as compared to results obtained with unprocessed speech. The algorithm takes advantage of a novel speech-detection algorithm recently developed at the University of British Columbia to classify individual signal segments as silence or speech; the coefficients of an adaptive filter are updated during signal periods classified as ‘silence’. Two variants of the least-mean square (LMS) algorithm, the leaky- and normalized-LMS, are integrated in the weight-update process to produce a noise-reduction scheme which adapts itself to the power of the input signal and also corrects for ill-conditioned inputs. The resulting speech-enhancement scheme is most effective with narrowband, quasi-stationary noises and robust under changing noise conditions. Although often used individually, to our knowledge the incorporation of both LMS variants into a single algorithm is unique to this research. Speech Perception in Noise (SPIN) tests were used on eight hearing-impaired subjects to evaluate the algorithm’s performance. Two types of noise background were used. Of the four subjects who heard motor noise, raw scores increased by 20 percent for the enhanced speech. These results were shown to be statistically significant using a two-way analysis of variance with repeated measures. However for those who heard babble or ‘cafeteria’ noise, the speech-enhancement process evidenced little improvement over scores from unprocessed speech. Further clinical evaluation is necessary, with a larger sample base, since the limited size of the study sample precluded assessing the algorithm with respect to specific subject factors such as degree or type of hearing loss.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat