Theoretical Analysis of Binaural Transfer Function MVDR Beamformers with Interference Cue Preservation Constraints

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

doi:10.1109/taslp.2015.2486381

Cited by 70 publications

(80 citation statements)

References 28 publications

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“…(2) and (3) exist for the target source. In addition, we quantify binaural spatial characteristics of the background noise in terms of the input and output magnitude square coherence (MSC) [5], [14] given by…”

Section: A Binaural Spatial Information Measuresmentioning

confidence: 99%

“…The binaural minimum variance distortionless response (BMVDR) beamformer [5] consists of two MVDR beamformers [12], [13] and requires only an estimate of the noise cross-power spectral density matrix and the RATF of the target. It provides the maximum noise reduction performance within the class of binaural linearly constrained distortionless minimum variance beamformers [5], [6].…”

Section: Introductionmentioning

confidence: 99%

“…It provides the maximum noise reduction performance within the class of binaural linearly constrained distortionless minimum variance beamformers [5], [6]. However, this is at the cost of distorting the binaural cues of the interferers [5], [6], which will coincide with the binaural cues of the target after processing [5]. The BMVDR-N method, initially proposed in [8] and further investigated in [14], combines the output of the BMVDR with a portion of the noisy unprocessed signal to preserve the binaural cues of the noise.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Binaural speech enhancement with spatial cue preservation utilising simultaneous masking

Koutrouvelis

Jensen

Guo

et al. 2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-Binaural multi-microphone noise reduction methods aim at noise suppression while preserving the spatial impression of the acoustic scene. Recently, a new binaural speech enhancement method was proposed which chooses per timefrequency (TF) tile either the enhanced target or a suppressed noisy version. The selection between the two is based on the input SNR per TF tile. In this paper we modify this method such that the selection mechanism is based on the output SNR. The proposed modification of deciding which TF tile is target-or noise-dominated leads to choices, which are better aligned with simultaneous masking properties of the auditory system, and, hence, improves the performance over the initial version of the algorithm.

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Section: A Binaural Spatial Information Measuresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Binaural speech enhancement with spatial cue preservation utilising simultaneous masking

Koutrouvelis

Jensen

Guo

et al. 2017

2017 25th European Signal Processing Conference (EUSIPCO)

View full text Add to dashboard Cite

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“…These algorithms are commonly designed by modifying the noise-reduction-related cost functions such that the binaural cues are kept undistorted [3,6,7]. It has been shown that the binaural multichannel Wiener filter (MWF) [8] and the binaural minimum-variance distortionlessresponse (MVDR) beamformer [9,10] can preserve the binaural cues of the speech components, whereas the binaural cues of the noise components will be distorted. To preserve the binaural cues of a directional noise source, the authors in [11] introduced a new parameter in MWF to facilitate a trade off between noise reduction and noise binaural cue preservation.…”

Section: Introductionmentioning

confidence: 99%

“…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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Binaural Speech Processing with Application to Hearing Devices

Doclo

Gannot

Marquardt

et al. 2018

Audio Source Separation and Speech Enhancement

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Theoretical Analysis of Binaural Transfer Function MVDR Beamformers with Interference Cue Preservation Constraints

Cited by 70 publications

References 28 publications

Binaural speech enhancement with spatial cue preservation utilising simultaneous masking

Binaural speech enhancement with spatial cue preservation utilising simultaneous masking

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

Binaural Speech Processing with Application to Hearing Devices

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