Theoretical Analysis of Linearly Constrained Multi-Channel Wiener Filtering Algorithms for Combined Noise Reduction and Binaural Cue Preservation in Binaural Hearing Aids

Marquardt, Daniel; Hadad, Elior; Gannot, Sharon; Doclo, Simon

doi:10.1109/taslp.2015.2479940

Cited by 56 publications

(36 citation statements)

References 24 publications

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“…This means that, unlike existing methods, the proposed method can preserve the binaural cues of more interferers than the number of microphones, while still achieving some noise reduction. Notice that a similar strategy to preserve the binaural cues in combination with a MWF has been proposed in [16] upon submission of the current paper.…”

Section: Resultsmentioning

confidence: 99%

Improved multi-microphone noise reduction preserving binaural cues

Koutrouvelis

Hendriks

Jensen

et al. 2016

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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We propose a new multi-microphone noise reduction technique for binaural cue preservation of the desired source and the interferers. This method is based on the linearly constrained minimum variance (LCMV) framework, where the constraints are used for the binaural cue preservation of the desired source and of multiple interferers. In this framework there is a trade-off between noise reduction and binaural cue preservation. The more constraints the LCMV uses for preserving binaural cues, the less degrees of freedom can be used for noise suppression. The recently presented binaural LCMV (BLCMV) method and the optimal BLCMV (OBLCMV) method require two constraints per interferer and introduce an additional interference rejection parameter. This unnecessarily reduces the degrees of freedom, available for noise reduction, and negatively influences the trade-off between noise reduction and binaural cue preservation. With the proposed method, binaural cue preservation is obtained using just a single constraint per interferer without the need of an interference rejection parameter. The proposed method can simultaneously achieve noise reduction and perfect binaural cue preservation of more than twice as many interferers as the BLCMV, while the OBLCMV can preserve the binaural cues of only one interferer.

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Section: Resultsmentioning

confidence: 99%

Improved multi-microphone noise reduction preserving binaural cues

Koutrouvelis

Hendriks

Jensen

et al. 2016

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…Later, a simplified MWF-ITF was proposed in [7] and offers a closed-form solution for binaural noise reduction and noise cue preservation. Moreover, additional linear constraints have been considered in the MVDR beamformer [10,15] and the binaural MWF [16,17] with the aim of preserving the binaural cues of an interfering source. Nevertheless, the techniques discussed so far are not well suited for the spatial preservation of diffuse noise.…”

Section: Introductionmentioning

confidence: 99%

Binaural noise reduction via cue-preserving MMSE filter and adaptive-blocking-based noise PSD estimation

Azarpour

Enzner

2017

EURASIP J. Adv. Signal Process.

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Binaural noise reduction, with applications for instance in hearing aids, has been a very significant challenge. This task relates to the optimal utilization of the available microphone signals for the estimation of the ambient noise characteristics and for the optimal filtering algorithm to separate the desired speech from the noise. The additional requirements of low computational complexity and low latency further complicate the design. A particular challenge results from the desired reconstruction of binaural speech input with spatial cue preservation. The latter essentially diminishes the utility of multiple-input/single-output filter-and-sum techniques such as beamforming. In this paper, we propose a comprehensive and effective signal processing configuration with which most of the aforementioned criteria can be met suitably. This relates especially to the requirement of efficient online adaptive processing for noise estimation and optimal filtering while preserving the binaural cues. Regarding noise estimation, we consider three different architectures: interaural (ITF), cross-relation (CR), and principal-component (PCA) target blocking. An objective comparison with two other noise PSD estimation algorithms demonstrates the superiority of the blocking-based noise estimators, especially the CR-based and ITF-based blocking architectures. Moreover, we present a new noise reduction filter based on minimum mean-square error (MMSE), which belongs to the class of common gain filters, hence being rigorous in terms of spatial cue preservation but also efficient and competitive for the acoustic noise reduction task. A formal real-time subjective listening test procedure is also developed in this paper. The proposed listening test enables a real-time assessment of the proposed computationally efficient noise reduction algorithms in a realistic acoustic environment, e.g., considering time-varying room impulse responses and the Lombard effect. The listening test outcome reveals that the signals processed by the blocking-based algorithms are significantly preferred over the noisy signal in terms of instantaneous noise attenuation. Furthermore, the listening test data analysis confirms the conclusions drawn based on the objective evaluation.

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“…A different category of binaural noise reduction methods is based on the multi-channel Wiener filter (MWF) framework [7], [8]. The MWF-based methods [9]- [11] can achieve higher signal-tonoise-ratio (SNR) gains, but unlike the LCMV, they typically distort the target signal. The binaural minimum variance distortionless response (BMVDR) BF [2] uses only two linear constraints to guarantee a distortionless response of the target at the two reference microphones.…”

Section: Introductionmentioning

confidence: 99%

Binaural beamforming using pre-determined relative acoustic transfer functions

Koutrouvelis

Hendriks

Heusdens

et al. 2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-Binaural beamformers (BFs) aim to reduce the output noise power while simultaneously preserving the binaural cues of all sources. Typically, the latter is accomplished via constraints relating the output and input interaural transfer functions (ITFs). The ITF is a function of the corresponding relative acoustic transfer function (RATF), which implies that RATF estimates of all sources in the acoustic scene are required. Here, we propose an alternative way to approximately preserve the binaural cues of the entire acoustic scene without estimating RATFs. We propose to preserve the binaural cues of all sources with a set of fixed pre-determined RATFs distributed around the head. Two recently proposed binaural BFs are evaluated in the context of using pre-determined RATFs and compared to the binaural minimum variance distrortionless response BF which can only preserve the binaural cues of the target.

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Theoretical Analysis of Linearly Constrained Multi-Channel Wiener Filtering Algorithms for Combined Noise Reduction and Binaural Cue Preservation in Binaural Hearing Aids

Cited by 56 publications

References 24 publications

Improved multi-microphone noise reduction preserving binaural cues

Improved multi-microphone noise reduction preserving binaural cues

Binaural noise reduction via cue-preserving MMSE filter and adaptive-blocking-based noise PSD estimation

Binaural beamforming using pre-determined relative acoustic transfer functions

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