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We introduce a new SVD-based (Singular value decomposition) strategy for noise reduction in hearing aids. This technique is evaluated for noise reduction in a behind-the-ear (BTE) hearing aid where two omnidirectional microphones are mounted in an endfire configuration. The behaviour of the SVD-based technique is compared to a two-stage adaptive beamformer for hearing aids developed by Vanden Berghe and Wouters (1998). The evaluation and comparison is done with a performance metric based on the speech intelligibility index (SII). The speech and noise signals are recorded in reverberant conditions with a signal-to-noise ratio of and the spectrum of the noise signals is similar to the spectrum of the speech signal. The SVD-based technique works without initialization nor assumptions about a look direction, unlike the two-stage adaptive beamformer. Still, for different noise scenarios, the SVD-based technique performs as well as the two-stage adaptive beamformer, for a similar filter length and adaptation time for the filter coefficients. In a diffuse noise scenario, the SVD-based technique performs better than the two-stage adaptive beamformer and hence provides a more flexible and robust solution under speaker position variations and reverberant conditions.

Abstract: This paper presents weighted approaches for integrated active noise control and noise reduction in hearing aids. The unweighted integrated active noise control and noise reduction scheme introduced in the previous work does not allow to trade-off between the active noise control and the noise reduction. In some circumstances it will, however, be useful to emphasize one of the functional blocks. Changing the original optimisation problem to a constrained optimisation problem leads to a scheme based on a weighted mean squared error criterion that allows to focus either on the active noise control or on the noise reduction. It is similarly possible to derive a scheme that allows to focus either on reducing the speech distortion or on reducing the residual noise at the eardrum. In a single speech source scenario and when the number of sound sources (speech plus noise sources) is less than or equal to the number of microphones, it is possible to derive a simple formula for the output signal-to-noise ratio of the latter scheme. It can then be shown that this scheme delivers a constant signal-to-noise ratio at the eardrum for any weighting factor. [Copyright &y& Elsevier]

Abstract: This paper analyses the output signal-to-noise ratio for a standard noise reduction scheme based on the multichannel Wiener filter and for an integrated active noise control and noise reduction scheme based on the filtered-X multichannel Wiener filter, both applied in a hearing aid framework that includes the effects of signal leakage through an open fitting and secondary path effects. In previous work, integrating noise reduction and active noise control has been shown to allow to compensate for effects of signal leakage and secondary path effects. These experimental results are now verified theoretically. The output signal-to-noise ratios are derived under a single speech source scenario. Theoretical results are then compared to simulations for a single noise source scenario and a multiple noise sources scenario. [Copyright &y& Elsevier]

Binaural hearing aids use microphone signals from both left and right hearing aid to generate an output signal for each ear. The microphone signals can be processed by a procedure based on speech distortion weighted multichannel wiener filtering (SDW-MWF) to achieve significant noise reduction in a speech + noise scenario. In binaural procedures, it is also desirable to preserve binaural cues, in particular the interaural time difference (ITD) and interaural level difference (ILD), which are used to localize sounds. It has been shown in previous work that the binaural SDW-MWF procedure only preserves these binaural cues for the desired speech source, but distorts the noise binaural cues. Two extensions of the binaural SDW-MWF have therefore been proposed to improve the binaural cue preservation, namely the MWF with partial noise estimation (MWF-η) and MWF with interaural transfer function extension (MWF-ITF). In this paper, the binaural cue preservation of these extensions is analyzed theoretically and tested based on objective performance measures. Both extensions are able to preserve binaural cues for the speech and noise sources, while still achieving significant noise reduction performance. [ABSTRACT FROM AUTHOR]

In a binaural hearing aid system, output signals need to be generated for the left and the right ear. Using the binaural multichannel Wiener filter (MWF), which exploits all microphone signals from both hearing aids, a significant reduction of background noise can be achieved. However, due to power and bandwidth limitations of the binaural link, it is typically not possible to transmit all microphone signals between the hearing aids. To limit the amount of transmitted information, this paper presents reduced-bandwidth MWF-based noise reduction algorithms, where a filtered combination of the contralateral microphone signals is transmitted. A first scheme uses a signal-independent beamformer, whereas a second scheme uses the output of a monaural MWF on the contralateral microphone signals and a third scheme involves an iterative distributed MWF (DB-MWF) procedure. It is shown that in the case of a rank-1 speech correlation matrix, corresponding to a single speech source, the DB-MWF procedure converges to the binaural MWF solution. Experimental results compare the noise reduction performance of the reduced-bandwidth algorithms with respect to the benchmark binaural MWF. It is shown that the best performance of the reduced-bandwidth algorithms is obtained by the DB-MWF procedure and that the performance of the DB-MWF procedure approaches quite well the optimal performance of the binaural MWF. [ABSTRACT FROM AUTHOR]

In this paper, solutions for combined feedback and noise suppression in hearing aids are developed. The techniques presented are based on the generalized sidelobe canceller (GSC) and adaptive feedback canceller (AFC), with a prediction error method (PEM) adaptation to avoid speech distortion. Two possible cascades of GSC-based noise reduction and AFC, namely an ldquoAFC firstrdquo and a ldquoGSC first,rdquo as well as a truly integrated solution that jointly suppresses feedback and noise are discussed. The integrated solution (called PEM-GFIC) achieves optimum synergies between noise and feedback suppression at the lowest computational cost. In addition, it cancels more feedback than the generalized echo and interference canceller, a joint solution for echo and noise suppression. In the cascaded solutions, the feedback and noise suppression filters are not always optimally exploited. For high input SNRs, ldquoAFC firstrdquo scheme generally may achieve better feedback cancellation because of its larger number of degrees of freedom. However, noise reduction by the GSC-stage seriously affects the feedback cancellation performance. At low SNRs, ldquoGSC firstrdquo generally achieves more feedback cancellation than PEM-GFIC at the expense of worse noise reduction. At high hearing aid gains and/or large SNRs, the noise reduction stage however negatively affects the performance of the feedback cancellation filter, resulting in a worse feedback and noise suppression compared to PEM-GFIC. [ABSTRACT FROM PUBLISHER]

Binaural hearing aids use microphone inputs from both the left and right hearing aid to generate an output for each ear. On the other hand, a monaural hearing aid generates an output by processing only its own microphone inputs. This correspondence presents a binstural extension of a monaural multichannel noise reduction algorithm for hearing aids based on Wiener filtering. In addition to significantly suppressing the noise interference, the algorithm preserves the interaural time delay (ITD) cues of the speech component, thus allowing the user to correctly localize the speech source. Unfortunately, binaural multichannel Wiener filtering distorts the ITD cues of the noise source. By adding a parameter :o the cost function the amount of noise reduction performed by the algorithm can be controlled, and traded off for the preservation of the noise ITO cues. [ABSTRACT FROM AUTHOR]

Abstract: Noise reduction (NR) and dynamic range compression (DRC) are basic components in hearing aids, but generally these components are developed and evaluated independently of each other. Hearing aids typically use a serial concatenation of NR and DRC. However, the DRC in such a concatenation negatively affects the performance of the NR stage: the residual noise after NR receives more amplification compared to the speech, resulting in a signal-to-noise-ratio (SNR) degradation. The integration of NR and DRC has not received a lot of attention so far. In this paper, a multi-channel Wiener filter (MWF)-based approach is presented for speech and noise scenarios, where an MWF-based NR algorithm is combined with DRC. The proposed solution is based on modifying the MWF and the DRC to incorporate the conditional speech presence probability in order to avoid residual noise amplification. The goal is then to analyse any undesired interaction effects by means of objective measures. Experimental results indeed confirm that a serial concatenation of NR and DRC degrades the SNR improvement provided by the NR, whereas the combined approach proposed here shows less degradation of the SNR improvement at a low increase in distortion compared to a serial concatenation. [Copyright &y& Elsevier]