Simon Doclo

Hearing4all

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Marc Moonen

KU Leuven

Henning Schepker

Starkey Hearing Technologies (United States)

Jan Wouters

KU Leuven

Toon van Waterschoot

KU Leuven

Daniel Marquardt

Praxis (United States)

Timo Gerkmann

Universität Hamburg

Ina Kodrasi

Idiap Research Institute

Stefan Goetze

University of Sheffield

Sharon Gannot

Bar-Ilan University

Ann Spriet

Universitair Ziekenhuis Leuven

Cooperative Institutions

Hearing4all

Carl von Ossietzky Universität Oldenburg

KU Leuven

Fraunhofer Institute for Digital Media Technology

Signal Processing (United States)

Institute of Electrical and Electronics Engineers

Aalborg University

Jade University of Applied Sciences

Imperial College London

Fraunhofer Society

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Model-based estimation of in-car-communication feedback applied to speech zone detection

arXiv (Cornell University) (2022)

Kaspar Müller Simon Doclo Jan Østergaard Tobias Barrington Wolff

Modern cars provide versatile tools to enhance speech communication. While an in-car communication (ICC) system aims at enhancing communication between the passengers by playing back desired speech via loudspeakers in the car, these loudspeaker signals may disturb a speech enhancement system required for hands-free telephony and automatic speech recognition. In this paper, we focus on speech zone detection, i.e. detecting which passenger in the car is speaking, which is a crucial component of the speech enhancement system. We propose a model-based feedback estimation method to improve robustness of speech zone detection against ICC feedback. Specifically, since the zone detection system typically does not have access to the ICC loudspeaker signals, the proposed method estimates the feedback signal from the observed microphone signals based on a free-field propagation model between the loudspeakers and the microphones as well as the ICC gain. We propose an efficient recursive implementation in the short-time Fourier transform domain using convolutive transfer functions. A realistic simulation study indicates that the proposed method allows to increase the ICC gain by about 6dB while still achieving robust speech zone detection results.

Robustness

10.48550/arxiv.2210.03363

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Average output SNR of the multichannel Wiener filter using statistical room acoustics

Toby Christian Lawin-Ore Simon Doclo

The performance of the multi-channel Wiener filter (MWF), which is often used for noise reduction in speech enhancement applications, depends on the noise field and on the acoustic transfer functions (ATFs) between the desired source and the microphone array. Recently, using statistical room acoustics an analytical expression for the spatially averaged output SNR, given the relative distance between the source and the microphone array, has been derived for the MWF in a diffuse noise field, requiring only the room properties to be known. In this paper, we show that this analytical expression can be extended to compute the average output SNR of the MWF for a specific microphone configuration, enabling to compare the performance of different microphone configurations, e.g. in an acoustic sensor network. Simulation results show that the average output SNR obtained using the statistical properties of ATFs is similar to the average output SNR obtained using simulated ATFs, therefore providing an efficient way to compare different microphone configurations.

Wiener filter

Room acoustics

10.1109/waspaa.2013.6701813

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補聴器における適応フィードバック制御のための改良された実用的な可変ステップサイズアルゴリズム【Powered by NICT】

IEEE Conference Proceedings (2016)

T T Tran Linh Schepker Henning Simon Doclo H Dam Hai Nordholm Sven

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Superdirective Beamforming Robust Against Microphone Mismatch

Simon Doclo Marc Moonen

Fixed superdirective beamformers using small-size microphone arrays are known to be highly sensitive to errors in the assumed microphone array characteristics. This paper discusses the design of robust superdirective beamformers by taking into account the statistics of the microphone characteristics. Different design procedures are considered: applying a white noise gain constraint, trading off the mean noise and distortion energy, and maximizing the mean or the minimum directivity factor. When computational complexity is not important, maximizing the mean or the minimum directivity factor is the preferred design procedure. In addition, it is shown how to determine a suitable parameter range for the other design procedures

Noise-canceling microphone

10.1109/icassp.2006.1661207

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THEORETICAL ANALYSIS OF BINAURAL CUE PRESERVATION USING MULTI-CHANNEL WIENER FILTERING AND INTERAURAL TRANSFER FUNCTIONS

Simon Doclo Thomas Klasen Tim Van den Bogaert Jan Wouters Marc Moonen

In this paper a theoretical analysis of the binaural cue preservation of the multi-channel Wiener filter (MWF) is performed. We will prove that in the case of a single speech source the MWF perfectly preserves the binaural cues of the speech component, but changes the binaural cues of the noise component to the cues of the speech component. In addition, we show that by extending the MWF cost function with terms related to the interaural transfer function it is possible to preserve the binaural cues of both the speech and the noise component, without considerably reducing the noise reduction performance.

Wiener filter

Component (thermodynamics)

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Citations (53)

Regularization Approaches for Synthesizing HRTF Directivity Patterns

IEEE/ACM Transactions on Audio Speech and Language Processing (2015)

Eugen Rasumow Martin Hansen Steven van de Par Dirk Püschel Volker Mellert

As an alternative to traditional artificial heads, it is possible to synthesize individual head-related transfer functions (HRTFs) using a so-called virtual artificial head (VAH), consisting of a microphone array with an appropriate topology and filter coefficients optimized using a narrowband least squares cost function. The resulting spatial directivity pattern of such a VAH is known to be sensitive to small deviations of the assumed microphone characteristics, e.g., gain, phase and/or the positions of the microphones. In many beamformer design procedures, this sensitivity is reduced by imposing a white noise gain (WNG) constraint on the filter coefficients for a single desired look direction. In this paper, this constraint is shown to be inappropriate for regularizing the HRTF synthesis with multiple desired directions and three alternative different regularization approaches are proposed and evaluated. In the first approach, the measured deviations of the microphone characteristics are taken into account in the filter design. In the second approach, the filter coefficients are regularized using the mean WNG for all directions. The third approach additionally takes into account several frequency bins into both the optimization and the regularization. The different proposed regularization approaches are compared using analytic and measured transfer functions, including random deviations. Experimental results show that the approach using multiple frequency bands mimicking the spectral resolution of the human auditory system yields the best robustness among the considered regularization approaches.

Regularization

Narrowband

Robustness

10.1109/taslp.2015.2504874

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Constrained multi-channel linear prediction for adaptive speech dereverberation

Ante Jukić Zichao Wang Toon van Waterschoot Timo Gerkmann Simon Doclo

This paper presents a speech dereverberation algorithm combining adaptive multi-channel linear prediction (MCLP) with a statistical model for the undesired reverberation. More specifically, we propose to constrain the power of the MCLP-based late reverberation estimate with the late reverberant power estimated using the exponential decay model, thereby preventing excessive cancellation of the speech signal. Simulation results show that incorporating the constraint improves the performance of the adaptive dereverberation method when the prediction filters need to adapt quickly.

Linear prediction

SIGNAL (programming language)

10.1109/iwaenc.2016.7602922

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NOISE ROBUST DISTANT AUTOMATIC SPEECH RECOGNITION UTILIZING NMF BASED SOURCE SEPARATION AND AUDITORY FEATURE EXTRACTION

Niko Moritz Marc René Schädler Kamil Adiloğlu Bernd T. Meyer Tim Jürgens

This paper describes our contribution to the 2 nd CHiME challenge and focuses on the small vocabulary task, i.e. track one. We present a robust system combination that involves source separation, auditory feature extraction and a modified automatic speech recognition back-end. The source separation code is based on a non-negative matrix factorization approach and the presented auditory feature extraction method uses 2D Gabor filter functions to extract spectral, temporal and spectro-temporal information of the speech signals. In addition we describe the modifications to our classification back-end and discuss the achieved results. On the final CHiME test set the proposed system achieves a maximum keyword recognition rate improvement of 50.25 % for the -6 dB SNR condition, for instance.

Non-negative Matrix Factorization

Source Separation

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

Simon Doclo Ren G. Dong Thomas Klasen Jan Wouters S. Haykin

Wiener filter

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Citations (8)

Physical and perceptual evaluation of the Interaural Wiener Filter algorithm