No abstract

No difference in signal-to-noise ratio improvement was observed between hearing-impaired and normal-hearing listeners, although individual SRT levels may differ. On average, an SRT improvement of 7.7 and 3.9 dB for a single noise source at 90 degrees and 5.9 and 3.4 dB for two noise sources at 90 degrees and 270 degrees was obtained for both normal-hearing and hearing-impaired listeners, using the adaptive beamformer and the directional microphone, respectively, relative to the omnidirectional microphone signal. In diffuse noise, only small improvements were obtained.

These improvements in signal-to-noise ratio can be of great benefit for hearing aid users, who have difficulties with speech understanding in noisy environments.

In this paper, the first real-time implementation and perceptual evaluation of a singular value decomposition (SVD)-based optimal filtering technique for noise reduction in a dual microphone behind-the-ear (BTE) hearing aid is presented. This evaluation was carried out for a speech weighted noise and multitalker babble, for single and multiple jammer sound source scenarios. Two basic microphone configurations in the hearing aid were used. The SVD-based optimal filtering technique was compared against an adaptive beamformer, which is known to give significant improvements in speech intelligibility in noisy environment. The optimal filtering technique works without assumptions about a speaker position, unlike the two-stage adaptive beamformer. However this strategy needs a robust voice activity detector (VAD). A method to improve the performance of the VAD was presented and evaluated physically. By connecting the VAD to the output of the noise reduction algorithms, a good discrimination between the speech-and-noise periods and the noise-only periods of the signals was obtained. The perceptual experiments demonstrated that the SVD-based optimal filtering technique could perform as well as the adaptive beamformer in a single noise source scenario, i.e., the ideal scenario for the latter technique, and could outperform the adaptive beamformer in multiple noise source scenarios.