Nearfield Acoustic Holography using sparsity and compressive sampling principles

Regularization of the inverse problem is a complex issue when using Near-field Acoustic Holography (NAH) techniques to identify the vibrating sources. This paper shows that, for convex homogeneous plates with arbitrary boundary conditions, new regularization schemes can be developed, based on the sparsity of the normal velocity of the plate in a well-designed basis, i.e. the possibility to approximate it as a weighted sum of few elementary basis functions. In particular, these new techniques can handle discontinuities of the velocity field at the boundaries, which can be problematic with standard techniques. This comes at the cost of a higher computational complexity to solve the associated optimization problem, though it remains easily tractable with out-of-the-box software. Furthermore, this sparsity framework allows us to take advantage of the concept of Compressive Sampling: under some conditions on the sampling process (here, the design of a random array, which can be numerically and experimentally validated), it is possible to reconstruct the sparse signals with significantly less measurements (i.e., microphones) than classically required. After introducing the different concepts, this paper presents numerical and experimental results of NAH with two plate geometries, and compares the advantages and limitations of these sparsity-based techniques over standard Tikhonov regularization.Comment: Journal of the Acoustical Society of America (2012

A review of cosparse signal recovery methods applied to sound source localization

National audienceThis work aims at comparing several state-of-the-art methods for cosparse signal recovery, in the context of sound source localization. We assess the performance of ve cosparse recovery algorithms: Greedy Analysis Structured Pursuit, l1 and joint l1,2 minimization, Structured Analysis Iterative Hard Thresholding and Structured Analysis Hard Thresholding Pursuit. In addition, we evaluate the performance of these methods against the sparse synthesis paradigm, solved with corresponding joint l1,2 minimization method. For this evaluation, the chosen applicative showcase is sound source localization from simulated measurements of the acoustic pressure eld.L'objectif de cet article est de comparer plusieurs m ethodes de l' etat de l'art pour la reconstruction coparcimonieuse de signaux, dans le contexte de la localisation de sources sonores. Nous evaluons les performances de cinq algorithmes de reconstruction coparcimonieuse : l'algorithme de "Greedy Analysis Structured Pursuit", les minimisations l1 et l1,2 jointe, ainsi que les algorithmes "Structured Analysis Iterative Hard Thresholding" et "Structured Analysis Hard Thresholding Pursuit". Nous comparons egalement ces algorithmes a l'approche de parcimonie a la synth ese, que nous r esolvons par la minimisation jointe l1,2 correspondante. Nous illustrons nos r esultats dans le cadre d'une application a la localisation de sources sonores, r ealise sur des simulations de mesures de champs de pression acoustique

Sparse underwater acoustic imaging: a case study

International audienceUnderwater acoustic imaging is traditionally performed with beam- forming: beams are formed at emission to insonify limited angular regions; beams are (synthetically) formed at reception to form the image. We propose to exploit a natural sparsity prior to perform 3D underwater imaging using a newly built flexible-configuration sonar device. The computational challenges raised by the high- dimensionality of the problem are highlighted, and we describe a strategy to overcome them. As a proof of concept, the proposed approach is used on real data acquired with the new sonar to obtain an image of an underwater target. We discuss the merits of the obtained image in comparison with standard beamforming, as well as the main challenges lying ahead, and the bottlenecks that will need to be solved before sparse methods can be fully exploited in the context of underwater compressed 3D sonar imaging

First applications of sound-based control on a mobile robot equipped with two microphones

International audience— This paper validates experimentally a novel approach to robot audition, sound-based control, which consists in introducing auditory features directly as inputs of a closed-loop control scheme, that is, without any explicit localization process. The applications we present rely on the implicit bearings of the sound sources computed from the time difference of arrival (TDOA) between two microphones. By linking the motion of the robot to the aural perception of the environment, this approach has the benefit of being more robust to reverberation and noise. Therefore neither complex tracking method such as Kalman filtering nor TDOA enhancement with denoising or dereverberation methods are needed to track the correct TDOA measurements. The experiments conducted on a mobile robot instrumented with a pair of microphones show the validity of our approach. In a reverberating and noisy room, this approach is able to orient the robot to a mobile sound source in real time. A positioning task with respect to two sound sources is also performed while the robot perception is disturbed by altered and spurious TDOA measurements

Two nonnegative matrix factorization methods for polyphonic pitch transcription

2007 Music Information Retrieval Evaluation eXchange (MIREX)International audiencePolyphonic pitch transcription consists of estimating the onset time, duration and pitch of each note within a music signal. Adaptive signal models such as Nonnegative Matrix Factorization (NMF) appear well suited to this task, since they can provide a meaningful representation whatever instruments are playing. In this paper, we propose a simple transcription method using minimum residual loudness NMF, harmonic comb-based pitch identification and threshold-based onset/offset detection, and investigate a second method incorporating harmonicity constraints in the NMF model. Both methods are evaluated in the framework of MIREX 2007

Binaural auditory interaction without HRTF for humanoid robots: A sensor-based control approach

International audienceNo abstrac

The best of both worlds: synthesis-based acceleration for physics-driven cosparse regularization

International audienceRecently, a regularization framework for ill-posed inverse problems governed by linear partial differential equations has been proposed. Despite nominal equivalence between sparse synthesis and sparse analysis regularization in this context , it was argued that the latter is preferable from computational point of view (especially for huge scale optimization problems arising in physics-driven settings). However, the synthesis-based optimization benefits from simple, but effective all-zero initialization, which is not straightforwardly applicable in the analysis case. In this work we propose a multiscale strategy that aims at exploiting computational advantages of both regularization approaches

The DESAM toolbox: spectral analysis of musical audio

International audienceIn this paper is presented the DESAM Toolbox, a set of Matlab functions dedicated to the estimation of widely used spectral models for music signals. Although those models can be used in Music Information Retrieval (MIR) tasks, the core functions of the toolbox do not focus on any specific application. It is rather aimed at providing a range of state-of-the-art signal processing tools that decompose music files according to different signal models, giving rise to different ``mid-level'' representations. After motivating the need for such a toolbox, this paper offers an overview of the overall organization of the toolbox, and describes all available functionalities

MAPS - A piano database for multipitch estimation and automatic transcription of music

MAPS -- standing for MIDI Aligned Piano Sounds -- is a database of MIDI-annotated piano recordings. MAPS has been designed in order to be released in the music information retrieval research community, especially for the development and the evaluation of algorithms for single-pitch or multipitch estimation and automatic transcription of music. It is composed by isolated notes, random-pitch chords, usual musical chords and pieces of music. The database provides a large amount of sounds obtained in various recording conditions.MAPS (MIDI Aligned Piano Sounds) est une base de données de sons de pianos enregistrés et annotés sous format MIDI. MAPS a été conçue pour la recherche d'information musicale et a vocation à être utilisée dans la communauté de chercheurs associée. Elle est tout particulièrement appropriée pour le développement et l'évaluation d'algorithmes d'estimation de fréquences fondamentales simples ou multiples et de transcription automatique de la musique. Elle comporte des enregistrements de notes isolées, d'accords aléatoires, d'accords usuels et de morceaux du répertoire de piano, proposés dans différentes conditions d'enregistrement

Brain source localization using a physics-driven structured cosparse representation of EEG signals

International audienceLocalizing several potentially synchronous brain activities with low signal-to-noise ratio from ElectroEncephaloGraphic (EEG) recordings is a challenging problem. In this paper we propose a novel source localization method, named CoRE, which uses a Cosparse Representation of EEG signals. The underlying analysis operator is derived from physical laws satisfied by EEG signals, and more particularly from Poisson's equation. In addition, we show how physiological constraints on sources, leading to a given space support and fixed orientations for current dipoles, can be taken into account in the optimization scheme. Computer results, aiming at showing the feasability of the CoRE technique, illustrate its superiority in terms of estimation accuracy over dictionary-based sparse methods and subspace approaches