Jacob Benesty

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Verified

Jacob verified their affiliation via an institutional email.

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• PhD
• Professor at National Institute of Scientific Research

Linear system identification is a key problem in many important applications, among which echo cancellation is a very challenging one. Due to the long length impulse responses (i.e., echo paths) to be identified, there is always room (and needs) to improve the performance of the echo cancellers, especially in terms of complexity, convergence rate,...

Differential beamformers with small-size microphone arrays are very attractive for audio and speech signal acquisition thanks to their high directivity and frequency-invariant spatial responses. However, such beamformers often suffer from significant white noise amplification at low frequencies, which makes their implementation in real-world system...

The superdirective beamformer, while attractive for processing broadband acoustic signals, often suffers from the problem of white noise amplification. So, its application requires well-designed acoustic arrays with sensors of extremely low self-noise level, which is difficult if not impossible to attain. In this paper, a new binaural superdirectiv...

A wide variety of system identification problems can be efficiently addressed based on the Kronecker product decomposition of the impulse response, together with low-rank approximations. Such an approach solves the original system identification problem using a combination of two shorter filters. In this paper, targeting a higher dimensionality red...

This book explains the motivation for using microphone arrays as opposed to using a single sensor for sound acquisition. The book then goes on to summarize the most useful ideas, concepts, results, and new algorithms therein. The material presented in this work includes analysis of the advantages of using microphone arrays, including dimensionality...

Accurate modeling and analysis of a radiator mounted on an infinite baffle are crucial for understanding its acoustic radiation characteristics. This paper investigates the radiation behavior of a convex dome-shaped radiator in such a condition, showing that, under the farfield approximation, the pressure field is the three-dimensional Fourier tran...

The performance of deep learning-based multi-channel speech enhancement methods often deteriorates when the geometric parameters of the microphone array change. Traditional approaches to mitigate this issue typically involve training on multiple microphone arrays, which can be costly. To address this challenge, we focus on uniform circular arrays a...

In this work, we present a new perspective on the origin and interpretation of adaptive filters. By applying Bayesian principles of recursive inference from the state-space model and using a series of simplifications regarding the structure of the solution, we can present, in a unified framework, derivations of many adaptive filters which depend on...

This paper reviews pioneering works in microphone array processing and multichannel speech enhancement, highlighting historical achievements, technological evolution, commercialization aspects, and key challenges. It provides valuable insights into the progression and future direction of these areas. The paper examines foundational developments in...

Microphone array signal processing is significantly influenced by array parameters such as the number of sensors, array aperture, and array topology. These factors affect both the development of algorithms and their performance limitations. Consequently, applying algorithms designed for one array geometry to signals captured by different geometries...

Beamforming is a fundamental technique for extracting a speech signal of interest from noisy observations and is widely used in speech processing, communication, and recognition applications. Typically, microphone array beamforming is performed in the short-time Fourier transform (STFT) domain, where a distinct beamformer is designed and applied to...

This paper investigates the design of adaptive differential beamforming using small-spacing linear microphone arrays. We express the differential beamformer as a linear function of the target beampattern coefficients through orthogonal polynomial expansions. Consequently, the design of the beamformer reduces to optimizing these coefficients. To ens...

The significance of the coherent-to-diffuse-power ratio (CDR) has grown in the fields of speech dereverberation and noise reduction. However, existing CDR estimators are typically limited to applications with only two microphones. In this paper, we investigate CDR estimation in multichannel acoustic systems with more than two microphones. We propos...

The recently developed iterative Wiener filter using a fourth-order tensorial (FOT) decomposition owns appealing performance in the identification of long length impulse responses. It relies on the nearest Kronecker product representation (with particular intrinsic symmetry features), together with low-rank approximations. Nevertheless, this new it...

Beamforming has been used in a wide range of applications to extract the signal of interest from microphone array observations, which consist of not only the signal of interest, but also noise, interference, and reverberation. The recently proposed interference-controlled maximum noise reduc- tion (ICMR) beamformer provides a flexible way to contro...

Distributed acoustic sensor network (DASN) refers to a sound acquisition system that consists of a collection of microphones randomly distributed across a wide acoustic area. Theory and methods for DASN are gaining increasing attention as the associated technologies can be used in a broad range of applications to solve challenging problems. However...

We show how to find automatically the regularization parameter in the MMSE problem

For system identification problems associated with long-length impulse responses, the recently developed decomposition-based technique that relies on a third-order tensor (TOT) framework represents a reliable choice. It is based on a combination of three shorter filters, which merge their estimates in tandem with the Kronecker product. In this way,...

In linear system identification problems, the Wiener filter represents a popular tool and stands as an important benchmark. Nevertheless, it faces significant challenges when identifying long-length impulse responses. In order to address the related shortcomings, the solution presented in this paper is based on a third-order tensor decomposition te...

Acoustic echo cancellation (AEC) is a crucial task in full duplex communications. As conventional linear filtering approaches are ineffective to deal with double-talk, various semi-blind source separation (SBSS)-based AEC algorithms are deceived, most of which are formulated and implemented in the frequency domain based on the multiplicative transf...

Linear differential microphone arrays (LDMAs) are commonly integrated into thin and portable devices to achieve high-fidelity speech acquisition. Traditional LDMAs typically consist of only omnidirectional microphones, which impose limitations on their ability to produce steerable spatial responses due to constraints in array element directivity an...

Direction-of-arrival (DOA) estimation is challenging in complex acoustic environments with background noise and interference. Utilizing spherical microphone arrays, closed-form estimators can be derived, which are attractive for practical applications due to their computational efficiency, eliminating the need for exhaustive extremum searching. How...

Differential microphone arrays (DMAs), which enhance acoustic signals of interest by measuring both the acoustic pressure field and its spatial derivatives, find extensive use in various practical systems and acoustic products. A critical element of DMAs is the differential beamformer, traditionally designed to ensure that the designed beampattern...

In this paper, we present a novel single-input/binaural-output (SIBO) minimum variance distortionless response (MVDR) noise reduction method, which involves formulating two MVDR sub-filters, one for the left ear and the other for the right ear, by minimizing the interaural coherence of the noise signal while ensuring the distortionless constraint,...

In this paper, a stochastic model is presented for the nonparametric variable step-size normalized least-mean-square (NP-VSS-NLMS) algorithm. This algorithm has demonstrated potential in practical applications and hence a deeper understanding of its behavior becomes crucial. In this context, model expressions are obtained for characterizing the alg...

Concentric circular microphone arrays have been used in a wide range of applications, such as teleconferencing systems and smarthome devices for speech signal acquisition. Such arrays are generally designed with omnidirectional sensors, and the associated beamformers are fully steerable but only in the sensors' plane. If operated in the three-dimen...

The image model method has been widely used to simulate room impulse responses and the endeavor to adapt this method to different applications has also piqued great interest over the last few decades. This paper attempts to extend the image model method and develops an anchor-point-image-model (APIM) approach as a solution for simulating impulse re...

Nature is usually low rank! This means that there is nonnegligible redundancy in the observations. So, it is important to be able to translate this idea into equations in order to make things work better in practice. In this chapter, we discuss this concept and explain how it can be applied to beamforming. Then, we derive a large class of low-rank...

In this chapter, we study beamforming with very large arrays, i.e., arrays that contain a very large number of microphones. Conventional beamforming in this context, where a simple complex frequency-dependent weight is applied to each microphone, may not be very practical for obvious reasons such as high complexity, difficulty to accurately estimat...

Single microphone processing is a very popular technique in speech enhancement. It has been studied for several decades and has been implemented in many systems. This method has, obviously, great limitations. In this chapter, we explain why and show the importance of spatial information (with just two microphones) to fully understand why it leads t...

Distortionless beamforming plays a huge role in microphone array processing, in particular, and array processing, in general. Indeed, the most interesting and practical (fixed or adaptive) beamformers are distortionless. Therefore, it is of interest to study this important family of beamformers and understand how they really work. This is the objec...

In this chapter, we give a fresh perspective on binaural beamforming, where within the same process, we also try to take advantage of our binaural hearing system. Basically, after beamforming, we wish to place the desired speech signal and noise in different positions in the perceptual space in order to possibly improve intelligibility as compared...

Principal component analysis (PCA) is by far the most popular and useful dimensionality reduction technique that one can find in the literature. The objective of PCA is the reduction of the dimension of a random signal vector from M to P, where \(P \ll M\), with little loss of the useful information. It does so by preserving the variability of the...

Another fundamental way to perform beamforming is by considering pressure differences among microphones instead of direct pressure as in conventional beamforming. This leads to the co-called differential beamforming with at least two great advantages: frequency-invariant beampatterns and high directional gains. Although there are different strategi...

After a brief but insightful discussion on the limitations of single microphone processing and the unquestionable advantages of spatial information, in this chapter, we make a concise overview of the most fundamental concepts in microphone array processing. We start with the signal model by considering the general case of three-dimensional arrays....

In some applications, it may be more convenient to find a noise reference, which can then be used to adaptively cancel the additive noise at microphones. This chapter is concerned with this problem. Furthermore, as it will be explained, adaptive noise cancellation gives another insightful perspective of distortionless adaptive beamforming.KeywordsA...

This work focuses on linear system identification problems in the framework of the Wiener filter. Specifically, it addresses the challenging identification of systems characterized by impulse responses of long length, which poses significant difficulties due to the existence of large parameter space. The proposed solution targets a dimensionality r...

This paper studies the problem of target speaker signal exaction and antiphasic rendering with an array of microphones in the scenarios where there are two active speakers. Based on the important findings achieved in the psychoacoustic field as well as our recent works on single-channel speech enhancement, we present a rendering based approach in w...

Stereophonic audio devices employ two loudspeakers and two microphones in order to create a bidirectional sound effect. In this context, the stereophonic acoustic echo cancellation (SAEC) setup requires the estimation of four echo paths, each one corresponding to a loudspeaker-to-microphone pair. The widely linear (WL) model was proposed in recent...

This paper studies the design of maximum directivity factor (MDF) beamformers based on uniform linear arrays (ULAs) consisting of acoustic vector sensors (AVSs). We first derive the main lobe constraints, which ensure that the beamformer's beampattern achieves a maximum in the look direction, and prove that any beamformer that satisfies the propose...

This paper is dedicated to the design of fully steerable linear differential microphone arrays (LDMAs). We analyze the steerable ideal spatial responses and explain why conventional LDMAs consisting of only omnidirectional microphones have limited steering ability. In order to circumvent this limitation, we suggest to use both omnidirectional and b...

Differential microphone arrays (DMAs) have demonstrated a great potential for high-fidelity acoustic and speech signal acquisition in a wide range of applications since such arrays are able to achieve frequency-invariant beampatterns with high directivity. Consequently, a great number of efforts have been devoted to the design of DMAs and the assoc...

Differential microphone arrays (DMAs) have demonstrated a great potential for solving the high-fidelity sound acquisition problem in a wide range of applications as they possess many good properties such as frequency-independent beampatterns with high directivity. A significant number of efforts have been devoted to the design of DMAs and the assoc...

A room Acoustic Impulse Response (RAIR), which represents the sound propagation channel via direct and reflection paths from a source position to a microphone, plays a leading role in a broad range of acoustic signal processing applications, e.g., echo cancellation. In practical acoustic environments, it is not uncommon that an RAIR may consist of...

The identification of long-length impulse responses represents a challenge in the context of many applications, like echo cancellation. Recently, the problem has been addressed in the framework of low-rank systems, using a decomposition of the impulse response based on the nearest Kronecker product and low-rank approximations. As a result, the orig...

This paper presents a stochastic model for the least-mean-square algorithm with symmetric/antisymmetric properties (LMS-SAS), operating in a system identification setup with Gaussian input data. Specifically, model expressions are derived to describe the mean weight behavior of the (global and virtual) adaptive filters, learning curves, and evoluti...