Conference Paper

Extension of the multi-channel Wiener filter with ITD cues for noise reduction in binaural hearing aids

Dept. of Electr. Eng., Katholieke Univ., Leuven
DOI: 10.1109/ASPAA.2005.1540171 Conference: Applications of Signal Processing to Audio and Acoustics, 2005. IEEE Workshop on
Source: IEEE Xplore


This paper presents a novel extension of the multi-channel Wiener filter (MWF) for noise reduction in binaural hearing aids, taking into account binaural localisation cues. By adding a term related to the interaural time difference (ITD) cue of the noise component to the cost function of the MWF, both the ITD cues of the speech and the noise component can be preserved, in addition to significantly improving the signal-to-noise ratio of the microphone signals

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Available from: Jan Wouters
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    • "traffic) even dangerous for the hearing aid user. To optimally benefit from binaural unmasking and to preserve the spatial impression for the hearing aid user, several extensions of the binaural MWF have been proposed, which aim to also preserve the binaural cues of the residual noise component by including cue preservation terms in the binaural MWF cost function [20], [25], [27]. However, for all proposed binaural MWF extensions, a trade-off between noise reduction performance and binaural cue preservation exists and by design, MWF-based algorithms suffer from some distortion of the desired source. "
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    ABSTRACT: The objective of binaural noise reduction algorithms is not only to selectively extract the desired speaker and to suppress interfering sources (e.g., competing speakers) and ambient background noise, but also to preserve the auditory impression of the complete acoustic scene. For directional sources this can be achieved by preserving the relative transfer function (RTF) which is defined as the ratio of the acoustical transfer functions relating the source and the two ears and corresponds to the binaural cues. In this paper, we theoretically analyze the performance of three algorithms that are based on the binaural minimum variance distortionless response (BMVDR) beamformer, and hence, process the desired source without distortion. The BMVDR beamformer preserves the binaural cues of the desired source but distorts the binaural cues of the interfering source. By adding an interference reduction (IR) constraint, the recently proposed BMVDR-IR beamformer is able to preserve the binaural cues of both the desired source and the interfering source. We further propose a novel algorithm for preserving the binaural cues of both the desired source and the interfering source by adding a constraint preserving the RTF of the interfering source, which will be referred to as the BMVDR-RTF beamformer. We analytically evaluate the performance in terms of binaural signal-to-interference-and-noise ratio (SINR), signal-to-interference ratio (SIR), and signal-to-noise ratio (SNR) of the three considered beamformers. It can be shown that the BMVDR-RTF beamformer outperforms the BMVDR-IR beamformer in terms of SINR and outperforms the BMVDR beamformer in terms of SIR. Among all beamformers which are distortionless with respect to the desired source and preserve the binaural cues of the interfering source, the newly proposed BMVDR-RTF beamformer is optimal in terms of SINR. Simulations using acoustic transfer functions measured on a binaural hearing aid validate our theoretical results.
    Full-text · Article · Dec 2015 · IEEE Transactions on Audio Speech and Language Processing
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    • "Moreover, it requires the a priori knowledge about the interaural time and level differences of the source signal, which is difficult if not impossible to acquire in many applications such as teleconferencing. The third category is through the use of multichannel noise reduction principles such as the transfer function based generalized sidelobe canceller (TF-GSC) [17], the multichannel Wiener filter [18], and the spatio-temporal prediction method [19]. Since the multichannel noise reduction techniques are formulated to estimate the desired signals observed at the microphones, the spatial information should be naturally preserved . "
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    ABSTRACT: This paper deals with the problem of noise reduction in stereo sound systems where the objective is not only to reduce noise, but also to preserve the spatial information of both the desired speech and noise sources so that the listener can still localize the speech and noise sources by listening to the enhanced binaural outputs. To achieve this objective, we use the widely linear (WL) framework developed previously and convert the problem of binaural noise reduction into one of monaural filtering with complex signals. We then present a way to decompose both the complex speech and noise signal vectors into two orthogonal components: one correlated and the other uncorrelated with the corresponding current signal sample. With this decomposition, the problem of noise reduction with preservation of the spatial information of speech and noise sources is formulated as an optimization problem with two constraints: one on the desired speech and the other on the preservation of the noise signal. We then derive a WL linearly constrained minimum variance (LCMV) filter, which can take advantage of the statistics and noncircularity of the complex speech signal to achieve noise reduction. In contrast to the WL Wiener and minimum variance distortionless response (MVDR) filters developed previously that can only preserve the characteristics and spatial information of the desired sound source, this new WL LCMV filter has the potential to reduce noise while preserving the characteristics and spatial information of both the desired and noise sources at the same time. Experimental results are provided to justify the claimed merits of the proposed WL LCMV filter.
    Full-text · Article · Jul 2013 · IEEE Transactions on Audio Speech and Language Processing
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    • "Alternatively, instead of trying to determine a common gain, in a specific class of optimal multichannel frequency-domain algorithms (namely the Multichannel Wiener Filter), some solutions exist ([9] [10] [11], and other works cited in [11]) which instead try and constrain complex Wiener gains to minimize additional components in the global cost function which are aimed at reducing interaural time or level differences; however , we see some drawbacks in [9] [10] [11]: first the solutions are tailored to a binaural hearing aid configuration; next they require a potentially complex iterative optimization scheme for each incoming frame of noisy samples [11]. Finally, as reported in [11] in an extensive analysis, these solutions may not be robust to multiple-noise-source scenarios. "
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    ABSTRACT: It is often very important for multichannel speech enhancement systems, such as hearing aids, to preserve spatial impressions. Usually, this is achieved by first designing a particular speech enhancement algorithm and later or separately constraining the obtained solution to respect spatial cues. Instead, we propose in this paper to conduct the entire system's design via the minimization of statistical spectral distances seen as functions of a real-valued, common gain to be applied to all channels in the frequency-domain. For various spectral distances, we show that the gain derived is expressible in terms of optimal multichannel spectral amplitude estimators (such as the multichannel Minimum Mean Squared Error Spectral Amplitude Estimator, among others). In addition, we report experimental results in complex environments (i.e., including reverberation, interfering talkers, and low signal-to-noise ratio), showing the potential of the proposed methods against recent state-of-the-art multichannel enhancement setups which preserve spatial cues as well.
    Full-text · Article · Jan 2013 · Signal Processing
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