Block-sparse approach for the identification of complex sound sources in a room

International audienceGeometrical acoustic softwares are necessary to produce auralizations for specific sound environment. Whether the room impulse response computation require point-source and receiver to be of omnidirectional sensitivity, the influence of their directivity on the resulting virtual audio rendering Is relevant. It is then crucial to account for when simulating accurately a calibrate acoustic model.We treats here the case of the source directivity. The use of a spherical surrounding microphone array remains the most natural way to measure it. The source is located inside the delimiting volume. The radiated pressure is sampled at fixed points. The directivity pattern is then computed in term of spherical harmonics functions. But due to hardware complexity, most of the spherical antennas in the litterature have a few number of microphones. This limits the performance of the antenna in term of resolution and bandwidth. Also, decomposition errors can appear with a possible mismatch between the acoustic center of the source and the origin of the array. An additional optimization task is required which increases the complexity of the process.In this paper, we propose a practical strategy, comprising a dedicated algorithm and an array design, to estimate the directivity pattern of complex sound sources. The study takes place in reverberant rooms.Firstly, we describe a greedy-sparse algorithm called Block Orthogonal Matching Pursuit. By this iterative approach, the identification and characterization tasks can be joint in a unique scheme. This facilitates the acoustic center research. However, under non-anechoic conditions, BlockOMP fails because of the free-field propagation assumption. Considering the first reflections to approximate the room transfer function permits to solve the inverse problem. The notion of virtual microphone arrays, based on an analogy with the Image Source Method, is introduced to extend the validity of BlockOMP. Numerical results supply a proof of the concept in a scenario including multiple acoustic sources.Secondly, a large three-dimensional microphone array is deployed. Largeness concerns here in both its dimensions and the number of microphones. The array consists of five sub-planes which surround the entire room where sources are located. The acquisition system comprises digital MEMS microphones chips. The entire signal processing chain is directly integrated on the captor. The microphones are flush mounted on the walls of the room. The true location of the sensors is known, given by an acoustic geometrical calibration step. The 1024 MEMS record synchronously the pressure signal emitted by the sources. From each harmonic spectral component, a sparse spherical harmonics decomposition of each target can be achieved.An experiment is performed to assert the efficiency of the proposed strategy. The goal is to recover the nature of two prototypes of source. They are build from an unbaffled loudspeaker, arranged to show a dipole and a quadripole behaviour. Their directivity pattern are previously measured under controlled conditions using a semi-circular array of 64 microphones. This database serves here as reference. For the experiment, they emit the same signal simultaneous. The results with our system indicates good correlations. Separating both the sound radiating contribution is well achieved. Our last study case deals with the voice directivity measurements. If the dependence with the frequency has been established, the effect of the phonema variation is rarely identified. We demonstrate here that our apparatus constitutes a powerful tool to examine this aspect

Identification of complex acoustic sources under reverberant conditions using large scale microphone arrays

La directivité d'une source sonore intervient dans de nombreuses applications en acoustique, allant de la compréhension des phénomènes physiques aéro-acoustiques jusqu'à la reproduction sonore spatialisée. Pour estimer expérimentalement cette signature spatiale, il est d’usage de déployer les microphones de sorte à englober partiellement ou totalement les sources. Le rayonnement acoustique est ainsi capté dans toutes les directions de l'espace. Sur ce principe, nous proposons dans ce manuscrit le développement d'un réseau microphonique 3D de grandes dimensions. L'antenne baptisée MODO ("Les Murs Ont Des Oreilles") comprend un total de 1024 MEMS digitaux, répartis sur les murs et les parois d'une salle rectangulaire classique. Pour localiser les sources acoustiques et caractériser leur directivité, nous résolvons le problème inverse associé sous contrainte de parcimonie structurée. La méthode choisie exploite le faible nombre de sources dans la salle, autorisant une représentation parcimonieuse du champ sonore mesuré. Le formalisme des harmoniques sphériques est utilisé pour décomposer efficacement la directivité des sources et les composantes élémentaires de rayonnement qui la compose. Les trajets de propagation acoustique sont modélisés via l'intégration des fonctions de transfert de la salle, qui sont synthétisées grâce au principe des antennes virtuelles. Nous validons la méthode de caractérisation proposée sur des sources directives connues, dont la directivité est étalonnée au préalable à l'aide d'une antenne sphérique d'ordre élevé.Knowing the directivity pattern of an acoustic source is useful in many applications in acoustics. To experimentally estimate the spatial signature, it is common to deploy microphones partially or totally surrounding the source. The acoustic radiation is then captured in all possible directions. In this thesis, we discuss the development of a large-scale 3D microphone array. This array, named "MODO" ("Les Murs Ont Des Oreilles", or, "The Walls Have Ears"), is comprised of 1024 digital MEMS microphones, flush mounted on the walls and the ceiling of a typical shoe-box room. In order to localize the sources and identify their directivity pattern, we solve the associated inverse problem under block-sparsity constraints. The chosen method exploits the small number of sources inside the room, allowing a sparse representation of the measured sound field. We use the spherical harmonics formalism to efficiently describe the directivity of the sources and their individual contributions to the radiation pattern. The acoustic path is modelled via integration of room transfer functions, synthesized with the mirror microphone method. We validated the proposed characterization method \textit{in situ} by comparison with known directivity patterns, calibrated using a high order spherical microphone array in controlled conditions

Identification de sources acoustiques complexes en milieu réverbérant par grands réseaux de microphones

Knowing the directivity pattern of an acoustic source is useful in many applications in acoustics. To experimentally estimate the spatial signature, it is common to deploy microphones partially or totally surrounding the source. The acoustic radiation is then captured in all possible directions. In this thesis, we discuss the development of a large-scale 3D microphone array. This array, named "MODO" ("Les Murs Ont Des Oreilles", or, "The Walls Have Ears"), is comprised of 1024 digital MEMS microphones, flush mounted on the walls and the ceiling of a typical shoe-box room. In order to localize the sources and identify their directivity pattern, we solve the associated inverse problem under block-sparsity constraints. The chosen method exploits the small number of sources inside the room, allowing a sparse representation of the measured sound field. We use the spherical harmonics formalism to efficiently describe the directivity of the sources and their individual contributions to the radiation pattern. The acoustic path is modelled via integration of room transfer functions, synthesized with the mirror microphone method. We validated the proposed characterization method \textit{in situ} by comparison with known directivity patterns, calibrated using a high order spherical microphone array in controlled conditions.La directivité d'une source sonore intervient dans de nombreuses applications en acoustique, allant de la compréhension des phénomènes physiques aéro-acoustiques jusqu'à la reproduction sonore spatialisée. Pour estimer expérimentalement cette signature spatiale, il est d’usage de déployer les microphones de sorte à englober partiellement ou totalement les sources. Le rayonnement acoustique est ainsi capté dans toutes les directions de l'espace. Sur ce principe, nous proposons dans ce manuscrit le développement d'un réseau microphonique 3D de grandes dimensions. L'antenne baptisée MODO ("Les Murs Ont Des Oreilles") comprend un total de 1024 MEMS digitaux, répartis sur les murs et les parois d'une salle rectangulaire classique. Pour localiser les sources acoustiques et caractériser leur directivité, nous résolvons le problème inverse associé sous contrainte de parcimonie structurée. La méthode choisie exploite le faible nombre de sources dans la salle, autorisant une représentation parcimonieuse du champ sonore mesuré. Le formalisme des harmoniques sphériques est utilisé pour décomposer efficacement la directivité des sources et les composantes élémentaires de rayonnement qui la compose. Les trajets de propagation acoustique sont modélisés via l'intégration des fonctions de transfert de la salle, qui sont synthétisées grâce au principe des antennes virtuelles. Nous validons la méthode de caractérisation proposée sur des sources directives connues, dont la directivité est étalonnée au préalable à l'aide d'une antenne sphérique d'ordre élevé

Subjective Evaluation of Dynamic Voice Directivity for Auralizations

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Low incidence of SARS-CoV-2, risk factors of mortality and the course of illness in the French national cohort of dialysis patients

International audienceThe aim of this study was to estimate the incidence of COVID-19 disease in the French national population of dialysis patients, their course of illness and to identify the risk factors associated with mortality. Our study included all patients on dialysis recorded in the French REIN Registry in April 2020. Clinical characteristics at last follow-up and the evolution of COVID-19 illness severity over time were recorded for diagnosed cases (either suspicious clinical symptoms, characteristic signs on the chest scan or a positive reverse transcription polymerase chain reaction) for SARS-CoV-2. A total of 1,621 infected patients were reported on the REIN registry from March 16th, 2020 to May 4th, 2020. Of these, 344 died. The prevalence of COVID-19 patients varied from less than 1% to 10% between regions. The probability of being a case was higher in males, patients with diabetes, those in need of assistance for transfer or treated at a self-care unit. Dialysis at home was associated with a lower probability of being infected as was being a smoker, a former smoker, having an active malignancy, or peripheral vascular disease. Mortality in diagnosed cases (21%) was associated with the same causes as in the general population. Higher age, hypoalbuminemia and the presence of an ischemic heart disease were statistically independently associated with a higher risk of death. Being treated at a selfcare unit was associated with a lower risk. Thus, our study showed a relatively low frequency of COVID-19 among dialysis patients contrary to what might have been assumed