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Cochlear implant (CI) recipients report severe degradation of speech understanding under noisy conditions. Most CI recipients typically can require about 10–25 dB higher signal-to-noise ratio than normal hearing (NH) listeners in order to achieve similar speech understanding performance. In recent years, significant emphasis has been put on binaural algorithms, which not only make use of the head shadow effect, but also have two or more microphone signals at their disposal to generate binaural inputs. Most of the CI recipients today are unilaterally implanted but they can still benefit from the binaural processing utilizing a contralateral microphone. The phase error filtering (PEF) algorithm tries to minimize the phase error variance utilizing a time–frequency mask for noise reduction. Potential improvement in speech intelligibility offered by the algorithm is evaluated with four different kinds of mask functions. The study reveals that the PEF algorithm which uses a contralateral microphone but unilateral presentation provides considerable improvement in intelligibility for both NH and CI subjects. Further, preference rating test suggests that CI subjects can tolerate higher levels of distortions than NH subjects, and therefore, more aggressive noise reduction for CI recipients is possible. [ABSTRACT FROM PUBLISHER]

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 beamfonner in multiple noise source scenarios. [ABSTRACT FROM AUTHOR]