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This paper evaluates noise reduction techniques in bilateral and binaural hearing aids. Adaptive implementations (on a real-time test platform) of the bilateral and binaural speech distortion weighted multichannel Wiener filter (SDW-MWF) and a competing bilateral fixed beamformer are evaluated. As the SDW-MWF relies on a voice activity detector (VAD), a realistic binaural VAD is also included. The test subjects (both normal hearing subjects and hearing aid users) are tested by an adaptive speech reception threshold (SRT) test in different spatial scenarios, including a realistic cafeteria scenario with nonstationary noise. The main conclusions are: (a) The binaural SDW-MWF can further improve the SRT (up to 2 dB) over the improvements achieved by bilateral algorithms, although a significant difference is only achievable if the binaural SDW-MWF uses a perfect VAD. However, in the cafeteria scenario only the binaural SDW-MWF achieves a significant SRT improvement (2.6 dB with perfect VAD, 2.2 dB with real VAD), for the group of hearing aid users. (b) There is no significant degradation when using a real VAD at the input signal-to-noise ratio (SNR) levels where the hearing aid users reach their SRT. (c) The bilateral SDW-MWF achieves no SRT improvements compared to the bilateral fixed beamformer.

This paper presents a physical evaluation of four feedback cancellation techniques in commercial hearing aids and two implementations of a recently developed feedback cancellation algorithm. Based on physical measures for detecting instability, oscillations and distortion, three performance aspects were measured: 1) the added stable gain compared to the hearing aid operating without feedback reduction for white noise as well as for spectrally colored input signals in two static acoustic conditions, 2) the amount of feedback, oscillations and distortion at gain values below the maximum stable gain, 3) the ability to track feedback path changes. Added stable gains between 3 dB and 26 dB were identified. Five of the six techniques achieve worse feedback reduction for a tonal opera input signal than for a speech input signal. Preventing the feedback canceller to drift away from an initial feedback path measurement results in improved performance for tonal signals at the expense of a worse feedback reduction in the acoustic conditions that differ from the condition for which the initialization was performed, as well as a worse tracking of feedback path changes. Repeated measures indicated that the reproducibility of the test set-up is crucial, in particular when the hearing aid operates close to instability.

This paper evaluates speech enhancement in binaural multimicrophone hearing aids by noise reduction algorithms based on the multichannel Wiener filter (MWF) and the MWF with partial noise estimate (MWF-N). Both algorithms are specifically developed to combine noise reduction with the preservation of binaural cues. Objective and perceptual evaluations were performed with different speech-in-multitalker-babble configurations in two different acoustic environments. The main conclusions are as follows: (a) A bilateral MWF with perfect voice activity detection equals or outperforms a bilateral adaptive directional microphone in terms of speech enhancement while preserving the binaural cues of the speech component. (b) A significant gain in speech enhancement is found when transmitting one contralateral microphone signal to the MWF active at the ipsilateral hearing aid. Adding a second contralateral microphone showed a significant improvement during the objective evaluations but not in the subset of scenarios tested during the perceptual evaluations. (c) Adding the partial noise estimate to the MWF, done to improve the spatial awareness of the hearing aid user, reduces the amount of speech enhancement in a limited way. In some conditions the MWF-N even outperformed the MWF possibly due to an improved spatial release from masking.

This paper evaluates the influence of three multimicrophone noise reduction algorithms on the ability to localize sound sources. Two recently developed noise reduction techniques for binaural hearing aids were evaluated, namely, the binaural multichannel Wiener filter (MWF) and the binaural multichannel Wiener filter with partial noise estimate (MWF-N), together with a dual-monaural adaptive directional microphone (ADM), which is a widely used noise reduction approach in commercial hearing aids. The influence of the different algorithms on perceived sound source localization and their noise reduction performance was evaluated. It is shown that noise reduction algorithms can have a large influence on localization and that (a) the ADM only preserves localization in the forward direction over azimuths where limited or no noise reduction is obtained; (b) the MWF preserves localization of the target speech component but may distort localization of the noise component. The latter is dependent on signal-to-noise ratio and masking effects; (c) the MWF-N enables correct localization of both the speech and the noise components; (d) the statistical Wiener filter approach introduces a better combination of sound source localization and noise reduction performance than the ADM approach.

This paper studies the effect of bilateral hearing aids on directional hearing in the frontal horizontal plane. Localization tests evaluated bilateral hearing aid users using different stimuli and different noise scenarios. Normal hearing subjects were used as a reference. The main research questions raised in this paper are: (i) How do bilateral hearing aid users perform on a localization task, relative to normal hearing subjects? (ii) Do bilateral hearing aids preserve localization cues, and (iii) Is there an influence of state of the art noise reduction algorithms, more in particular an adaptive directional microphone configuration, on localization performance? The hearing aid users were tested without and with their hearing aids, using both a standard omnidirectional microphone configuration and an adaptive directional microphone configuration. The following main conclusions are drawn. (i) Bilateral hearing aid users perform worse than normal hearing subjects in a localization task, although more than one-half of the subjects reach normal hearing performance when tested unaided. For both groups, localization performance drops significantly when acoustical scenarios become more complex. (ii) Bilateral, i.e., independently operating hearing aids do not preserve localization cues. (iii) Overall, adaptive directional noise reduction can have an additional and significant negative impact on localization performance.

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.

Objective: The performance of an adaptive beam-former in a 2-microphone, behind-the-ear hearing aid for speech understanding in noisy environments was evaluated. Physical and perceptual evaluations were carried out. This was the first large-scale test of a wearable real-time implementation of this algorithm. The main perceptual research questions of this study were related to the influence on the noise reduction performance of (1) the spectro-temporal character of the jammer sound, (2) the jammer sound scene, (3) hearing impairment, and (4) the basic microphone configuration in the hearing aid. Four different speech materials were used for the perceptual evaluations. All tests were carried out in an acoustical environment comparable to living room reverberation., Design: The adaptive beamformer was implemented in Audallion, a small, body-worn processor, linked to a Danasound 2-microphone behind-the-ear aid. The strategy was evaluated physically in different acoustical environments. Using speech reception threshold (SRT) measurements, the processing was evaluated perceptually and the different research questions addressed with three groups of subjects. Groups I, II, and III consisted of 10 normal-hearing, 5 hearing-impaired, and 7 normal-hearing persons, respectively. The tests were carried out in three spectro-temporally different jammer sounds (unmodulated and modulated speech weighted noise, multitalker babble) and in three different noise scenarios (single noise source at 90 degrees, noise sources at 90 degrees and 270 degrees relative to speaker position, diffuse noise scene). Two microphone configurations were compared: a device equipped with two omnidirectional microphones and a device equipped with one hardware directional and one omnidirectional microphone. In each of these conditions, the adaptive beamformer and the directional and omnidirectional microphone configurations were tested., Results: The improvement in signal-to-noise ratio from the use of the adaptive beamformer did not depend on the spectro-temporal character of the jammer sounds and the speech materials used, although the absolute levels of the SRTs varied appreciably for different speech-noise combinations. The performance of the adaptive noise reduction depended on the jammer sound scene., Conclusions: 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., (Copyright 2004 Lippincott Williams and Wilkins)

An integrated version of the minimum variance distortionless response (MVDR) beamformer for speech enhancement using a microphone array has been recently developed, which merges the benefits of imposing constraints defined from both a relative transfer function (RTF) vector based on a priori knowledge and an RTF vector based on a data-dependent estimate. In this paper, the integrated MVDR beamformer is extended for use with a microphone configuration where a microphone array, local to a speech processing device, has access to the signals from multiple external microphones (XMs) randomly located in the acoustic environment. The integrated MVDR beamformer is reformulated as a quadratically constrained quadratic program (QCQP) with two constraints, one of which is related to the maximum tolerable speech distortion for the imposition of the a priori RTF vector and the other related to the maximum tolerable speech distortion for the imposition of the data-dependent RTF vector. An analysis of how these maximum tolerable speech distortions affect the behaviour of the QCQP is presented, followed by the discussion of a general tuning framework. The integrated MVDR beamformer is then evaluated with audio recordings from behind-the-ear hearing aid microphones and three XMs for a single desired speech source in a noisy environment. In comparison to relying solely on an a priori RTF vector or a data-dependent RTF vector, the results demonstrate that the integrated MVDR beamformer can be tuned to yield different enhanced speech signals, which may be more suitable for improving speech intelligibility despite changes in the desired speech source position and imperfectly estimated spatial correlation matrices. [ABSTRACT FROM AUTHOR]

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]

This paper presents combined active noise control and noise reduction schemes for hearing aids to tackle secondary path effects and effects of noise leakage through an open fitting. While such leakage contributions and the secondary acoustic path from the loudspeaker to the tympanic membrane are usually not taken into account in standard noise reduction systems, they appear to have a non-negligible impact on the final signal-to-noise ratio. Using a noise-reduction algorithm and an active noise control system in cascade may be efficient as long as the causality margin of the system is large enough. Putting the two functional blocks in parallel and then integrating them is found to lead to a more robust algorithm. A Filtered-x Multichannel Wiener Filter is presented and applied to integrate noise reduction and active noise control. The cascaded scheme and the integrated scheme are compared experimentally with a Multichannel Wiener Filter in a classic noise reduction framework without active noise control, where the integrated scheme is found to provide the best performance. [ABSTRACT FROM PUBLISHER]

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]

Users of a cochlear implant and contralateral hearing aid are sensitive to interaural level differences (ILDs). However, when using their clinical devices, most of these subjects cannot use ILD cues for localization in the horizontal plane. This is partly due to a lack of high-frequency residual hearing in the acoustically stimulated ear. Using acoustic simulations of a cochlear implant and hearing loss, it is shown that localization performance can be improved by up to 14° rms error relative to 48° rms error for broadband noise by artificially introducing ILD cues in the low frequencies. The algorithm that was used for ILD introduction is described. [ABSTRACT FROM AUTHOR]

Abstract: Acoustic feedback occurs in many audio applications involving musical sound signals. However, research efforts in acoustic feedback control have mainly been focused on speech applications. Since sound quality is of prime importance in audio applications, a proactive approach to acoustic feedback control is preferred to avoid ringing, howling, and excessive reverberation. Adaptive feedback cancellation (AFC) using a prediction-error-method (PEM)-based approach is a promising proactive solution, but existing algorithms are again designed for speech applications only. We propose to replace the all-pole near-end speech signal model in the PEM-based approach with a cascade of two near-end signal models: a tonal components model and a noise components model. We derive the identifiability conditions for joint identification of the acoustic feedback path and the cascaded near-end signal models. Depending on the model structure that is used for the near-end tonal components, three different PEM-based AFC algorithms are considered. By applying some relevant model approximations, the computational overhead of the proposed algorithms compared to the normalized least mean squares (NLMS) algorithm can be reduced to 25% of the NLMS complexity. Simulation results for both room acoustic and hearing aid scenarios indicate a significant performance improvement in terms of the misadjustment and the maximum stable gain increase. [Copyright &y& Elsevier]

Auditory steady-state responses (ASSRs) in EEG measurements are currently used for reliable hearing threshold estimation at audiometric frequencies. Especially, newborns with hearing problems benefit from this technique, as with this information, diagnosis can be better specified and hearing aids can be better fitted at an early age. Unfortunately, measurement duration is still very long for clinical widespread use due to the lack of efficient signal detection techniques with sufficient robustness against artifacts. In this paper, a simplified procedural framework for ASSR detection is worked out that allows the development of a multichannel processing strategy, starting from a detection theory approach. It is shown that a sufficient statistic can be calculated that best captures the amount of ASSR in the recorded data. The evaluation is conducted using data from ten normal-hearing adults. It is concluded that most single- and multichannel approaches are similar in performance when applied to uncontaminated EEG. When artifact-rich EEG is used, the proposed detection-theory-based approach significantly improves the number of ASSR detections compared with a noise-weighted common EEG channel derivation (vertex-occiput). [ABSTRACT FROM AUTHOR]

A multi-channel noise reduction technique is presented based on a Speech Distortion-Weighted Multi-channel Wiener Filter (SDW-MWF) approach that incorporates the conditional Speech Presence Probability (SPP). A traditional SDW-MWF uses a fixed parameter to a trade-off between noise reduction and speech distortion without taking speech presence into account. Consequently, the improvement in noise reduction comes at the cost of a higher speech distortion since the speech dominant segments and the noise dominant segments are weighted equally. Incorporating the conditional SPP in SDW-MWF allows to exploit the fact that speech may not be present at all frequencies and at all times, while the noise can indeed be continuously present. In speech dominant segments it is then desirable to have less noise reduction to avoid speech distortion, while in noise dominant segments it is desirable to have as much noise reduction as possible. Experimental results with hearing aid scenarios demonstrate that the proposed SDW-MWF incorporating the conditional SPP improves the signal-to-noise ratio compared to a traditional SDW-MWF. [ABSTRACT FROM AUTHOR]

The benefit of using external acoustic sensor nodes for noise reduction in hearing aids is demonstrated in a simulated acoustic scenario with multiple sound sources. A distributed adaptive node-specific signal estimation (DANSE) algorithm, that has a reduced communication bandwidth and computational load, is evaluated. Batch-mode simulations compare the noise reduction performance of a centralized multi-channelWiener filter (MWF) with DANSE. In the simulated scenario, DANSE is observed not to be able to achieve the same performance as its centralizedMWFequivalent, although in theory both should generate the same set of filters. A modification to DANSE is proposed to increase its robustness, yielding smaller discrepancy between the performance of DANSE and the centralized MWF. Furthermore, the influence of several parameters such as the DFT size used for frequency domain processing and possible delays in the communication link between nodes is investigated. [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]

The standard continuous adaptation feedback cancellation algorithm for feedback suppression in hearing aids suffers from a large model error or bias if the received sound signal is spectrally colored. To reduce the bias in the feedback path estimate, we propose adaptive feedback cancellation techniques that are based on a closed-loop identification of the feedback path as well as the (auto-regressive) modeling of the desired signal. In general, both models are not simultaneously identifiable in the closed-loop system at hand. We show that—under certain conditions, e.g., if a delay is inserted in the forward path—identification of both models is indeed possible. Two classes of adaptive procedures for identifying the desired signal model and the feedback path are derived: a two-channel identification method as well as a prediction error method. In contrast to the two-channel identification method, the prediction error method allows use of different adaptation schemes for the feedback path and for the desired signal model and, hence, is found to be preferable for highly non-stationary sound signals. Simulation results demonstrate that the proposed techniques outperform the standard continuous adaptation algorithm if the conditions for identifiability are satisfied. [ABSTRACT FROM AUTHOR]

For small-sized arrays such as hearing aids, noise reduction is obtained at the expense of an increased sensitivity to errors in the assumed signal model, i.e., microphone mismatch, variations in speaker and microphone positions, reverberation. However, the noise reduction algorithm should still be robust, i.e., insensitive to small signal model errors. In this paper, we evaluate the robustness of the Generalized Sidelobe Canceller (GSC) and a recently developed Multichannel Wiener Filtering (MWF) technique for hearing aid applications both analytically and experimentally. The analysis reveals that robustness of the GSC is especially crucial in complicated noise scenarios and that microphone mismatch is particularly harmful to the GSC, even when the adaptive noise canceller is adapted during noise only. Hence, a constraint on the noise sensitivity of the GSC is essential, at the expense of less noise reduction. The MWF on the other hand, is not affected by microphone mismatch and has a potential benefit over the robust GSC with noise sensitivity constraint. However, the MWF is sensitive to the estimation accuracy of the second order statistics of speech and noise so that its benefit may be lost in nonstationary noise scenarios. [ABSTRACT FROM AUTHOR]

Recently, a generalized noise reduction scheme has been proposed, called the Spatially Preprocessed, Speech Distortion Weighted, Multichannel Wiener Filter (SP-SDW-MWF). It encompasses the Generalized Sidelobe Canceller (GSC) and a multichannel Wiener filtering technique as extreme cases. Compared with the widely studied GSC with Quadratic Inequality Constraint (QICuGSC), the SP-SDW-MWF achieves a better noise reduction performance for a given maximum speech distortion level. In this paper, we develop a low-cost, stochastic gradient implementation of the SP-SDW-MWE To speed up convergence and reduce computational complexity, the algorithm is implemented in the frequency domain. Experimental results with a behind-the-ear hearing aid show that the proposed frequency-domain stochastic gradient algorithm preserves the benefit of the exact SP-SDW-MWF over the QIC-GSC, while its computational cost is comparable to the least mean square-based scaled projection algorithm for QIC-GSC. [ABSTRACT FROM AUTHOR]

Abstract: Double-talk (DT)-robust acoustic echo cancellation (AEC) and acoustic feedback cancellation (AFC) are needed in speech communication systems, e.g., in hands-free communication systems and hearing aids. In this paper, we derive a practical and computationally efficient algorithm based on the frequency-domain adaptive filter prediction error method using row operations (FDAF-PEM-AFROW) for DT-robust AEC and AFC. The proposed algorithm features two main modifications: (a) the Wiener variable step size (WVSS) and (b) the gradient spectral variance smoothing (GSVS). In AEC simulations, the WVSS-GSVS-FDAF-PEM-AFROW algorithm obtains outstanding robustness and smooth adaptation in highly adverse scenarios such as in bursting DT at high levels, and in a change of acoustic path during continuous DT. Similarly, in AFC simulations, the algorithm outperforms state-of-the-art algorithms when using a low-order near-end speech model and in colored non-stationary noise. [Copyright &y& Elsevier]

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]

Abstract: A user-friendly and versatile research platform for use in auditory experiments, referred to as APEX (Application for PsychoElectrical eXperiments), is described. The platform takes care of automatic stimulus presentation and collection of the subject''s responses. Acoustical auditory, as well as electrical auditory experiments with CI recipients can be conducted. The platform currently supports LAURA, Nucleus CI22 and Nucleus CI24 cochlear implants. The graphical user interface for the subjects has been extended to allow for testing very young children, by embedding the psychophysical procedures in a computer game. The research platform is available free of charge. [Copyright &y& Elsevier]

Abstract: Acoustic feedback is a well-known problem in hearing aids, caused by the undesired acoustic coupling between the hearing aid loudspeaker and microphone. Acoustic feedback produces annoying howling sounds and limits the maximum achievable hearing aid amplification. This paper is focused on adaptive feedback cancellation (AFC) where the goal is to adaptively model the acoustic feedback path and estimate the feedback signal, which is then subtracted from the microphone signal. The main problem in identifying the acoustic feedback path model is the correlation between the near-end signal and the loudspeaker signal caused by the closed signal loop, in particular when the near-end signal is spectrally colored as is the case for a speech signal. This paper adopts a prediction-error method (PEM)-based approach to AFC, which is based on the use of decorrelating prediction error filters (PEFs). We propose a number of improved PEF designs that are inspired by harmonic sinusoidal modeling and pitch prediction of speech signals. The resulting PEM-based AFC algorithms are evaluated in terms of the maximum stable gain (MSG), filter misadjustment, and computational complexity. Simulation results for a hearing aid scenario indicate an improvement up to 5–7dB in MSG and up to 6–8dB in terms of filter misadjustment. [Copyright &y& Elsevier]

Abstract: Recently, a generalized multi-microphone noise reduction scheme, referred to as the spatially pre-processed speech distortion weighted multichannel Wiener filter (SP-SDW-MWF), has been presented. This scheme consists of a fixed spatial pre-processor and a multichannel adaptive noise canceler (ANC) optimizing the SDW-MWF cost function. By taking speech distortion explicitly into account in the design criterion of the multichannel ANC, the SP-SDW-MWF adds robustness to the standard generalized sidelobe canceler (GSC). In this paper, we present a multichannel frequency-domain criterion for the SDW-MWF, from which several – existing and novel – adaptive frequency-domain algorithms can be derived. The main difference between these adaptive algorithms consists in the calculation of the step size matrix (constrained vs. unconstrained, block-structured vs. diagonal) used in the update formula for the multichannel adaptive filter. We investigate the noise reduction performance, the robustness and the tracking performance of these adaptive algorithms, using a perfect voice activity detection (VAD) mechanism and using an energy-based VAD. Using experimental results with a small-sized microphone array in a hearing aid, it is shown that the SP-SDW-MWF is more robust against signal model errors than the GSC, and that the block-structured step size matrix gives rise to a faster convergence and a better tracking performance than the diagonal step size matrix, only at a slightly higher computational cost. [Copyright &y& Elsevier]

Abstract: In this paper, a physical and perceptual evaluation of two adaptive noise reduction algorithms for dual-microphone hearing aids are described. This is the first comparison between a fixed directional microphone on the one hand, and an adaptive directional microphone and an adaptive beamformer on the other hand, all implemented in the same digital hearing aid. The adaptive directional microphone is state-of-the-art in most modern commercial hearing aids. The physical evaluation shows the importance of an individual calibration procedure for the performance of the noise reduction algorithms with two microphone hearing aids. The directivity index calculated in anechoic conditions and intelligibility-weighted polar diagrams measured in reverberant conditions show that all the noise reduction strategies yield an improved signal-to-noise ratio (SNR), but that the adaptive beamformer generally performs best. From the perceptual evaluation, it is demonstrated that the adaptive beamformer always performs best in single noise source scenarios. In a more complex noise scenario, there is still a SNR improvement with all the techniques, however the effect is the same for all the strategies. [Copyright &y& Elsevier]