Binaural Noise Cue Preservation in a Binaural Noise Reduction System With a Remote Microphone Signal

Szurley, Joseph; Bertrand, Alexander; Dijk, Bas van; Moonen, Marc

doi:10.1109/taslp.2016.2535199

Cited by 26 publications

(21 citation statements)

References 27 publications

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“…By computing the PSDs of the error signals according to (5), a system of equations including the left and right noise PSDs is obtained,…”

Section: Itf-based Adaptive Blocking (Itfb)mentioning

confidence: 99%

“…The error PSD e is obtained using the first-order recursive averaging according to (5), with E(λ, κ) being the STFT of the cross-relation error signal e(k) according to (19). By solving (26), the estimated noise PSD is obtained as…”

Section: Cr-based Adaptive Blocking (Crb)mentioning

confidence: 99%

“…The first category mostly consists of multichannel algorithms, therein combining spatial and spectral filtering, which attempt to reduce noise with an additional constraint on auditory scene preservation [3][4][5]. These algorithms are commonly designed by modifying the noise-reduction-related cost functions such that the binaural cues are kept undistorted [3,6,7].…”

Section: Introductionmentioning

confidence: 99%

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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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“…By computing the PSDs of the error signals according to (5), a system of equations including the left and right noise PSDs is obtained,…”

Section: Itf-based Adaptive Blocking (Itfb)mentioning

confidence: 99%

Section: Cr-based Adaptive Blocking (Crb)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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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“…To improve the performance of (binaural) algorithms in terms of noise reduction and source localization accuracy, it has been proposed to use an external microphone in conjunction with the head-mounted microphones [5][6][7][8][9][10][11][12]. For a diffuse noise field, an efficient RTF vector estimation method has been proposed in [11], This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -Project ID 352015383 (SFB 1330 B2) and Project ID 390895286 (EXC 2177/1).…”

Section: Introductionmentioning

confidence: 99%

RTF-Steered Binaural MVDR Beamforming Incorporating Multiple External Microphones

Gosling

Middelberg

Doclo

2019

2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)

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The binaural minimum-variance distortionless-response (BMVDR) beamformer is a well-known noise reduction algorithm that can be steered using the relative transfer function (RTF) vector of the desired speech source. Exploiting the availability of an external microphone that is spatially separated from the head-mounted microphones, an efficient method has been recently proposed to estimate the RTF vector in a diffuse noise field. When multiple external microphones are available, different RTF vector estimates can be obtained by using this method for each external microphone. In this paper, we propose several procedures to combine these RTF vector estimates, either by selecting the estimate corresponding to the highest input SNR, by averaging the estimates or by combining the estimates in order to maximize the output SNR of the BMVDR beamformer. Experimental results for a moving speaker and diffuse noise in a reverberant environment show that the output SNR-maximizing combination yields the largest binaural SNR improvement and also outperforms the state-of-the art covariance whitening method.

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“…In fact, existing systems that incorporate an external microphone with a communication link have already proven to provide benefits to HA and CI users [4][5][6][7]. More recently, in the context of an MVDR beamformer, NR strategies for using the external microphone signal have been proposed in [8][9][10]. In this paper, we focus on the extension of an MVDR beamformer that uses an external microphone signal to its GSC counterpart.…”

Section: Introductionmentioning

confidence: 99%

Generalised Sidelobe Canceller for Noise Reduction in Hearing Devices Using an External Microphone

Ali

Waterschoot

Moonen

2018

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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The use of an external microphone in conjunction with an existing local microphone array can be particularly beneficial for noise reduction tasks that are critical for hearing devices, such as cochlear implants and hearing aids. Recent work has already demonstrated how an external microphone signal can be effectively incorporated into the common noise reduction technique of using a Minimum Variance Distortionless Response (MVDR) beamformer. In this paper, we provide a further extension, whereby an external microphone signal can be incorporated into an existing framework of a Generalised Sidelobe Canceller (GSC) that has been designed for a local microphone signal array. It will be shown that the resulting GSC with an external microphone results in an easily implementable addition to the existing GSC framework for a local microphone array, and can exhibit an improved noise reduction performance.

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Binaural Noise Cue Preservation in a Binaural Noise Reduction System With a Remote Microphone Signal

Cited by 26 publications

References 27 publications

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

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

RTF-Steered Binaural MVDR Beamforming Incorporating Multiple External Microphones

Generalised Sidelobe Canceller for Noise Reduction in Hearing Devices Using an External Microphone

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