Relevant bibliographies by topics / Multiple sound sources localization

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Multiple sound sources localization'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 February 2022

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Journal articles on the topic "Multiple sound sources localization"

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Zhong, Xuan, Liang Sun, and William Yost. "Active binaural localization of multiple sound sources." Robotics and Autonomous Systems 85 (November 2016): 83–92. http://dx.doi.org/10.1016/j.robot.2016.07.008.

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Pu, Henglin, Chao Cai, Menglan Hu, Tianping Deng, Rong Zheng, and Jun Luo. "Towards Robust Multiple Blind Source Localization Using Source Separation and Beamforming." Sensors 21, no. 2 (2021): 532. http://dx.doi.org/10.3390/s21020532.

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Multiple blind sound source localization is the key technology for a myriad of applications such as robotic navigation and indoor localization. However, existing solutions can only locate a few sound sources simultaneously due to the limitation imposed by the number of microphones in an array. To this end, this paper proposes a novel multiple blind sound source localization algorithms using Source seParation and BeamForming (SPBF). Our algorithm overcomes the limitations of existing solutions and can locate more blind sources than the number of microphones in an array. Specifically, we propose a novel microphone layout, enabling salient multiple source separation while still preserving their arrival time information. After then, we perform source localization via beamforming using each demixed source. Such a design allows minimizing mutual interference from different sound sources, thereby enabling finer AoA estimation. To further enhance localization performance, we design a new spectral weighting function that can enhance the signal-to-noise-ratio, allowing a relatively narrow beam and thus finer angle of arrival estimation. Simulation experiments under typical indoor situations demonstrate a maximum of only 4∘ even under up to 14 sources.
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Liu, Chen, Bruce C. Wheeler, William D. O’Brien, Robert C. Bilger, Charissa R. Lansing, and Albert S. Feng. "Localization of multiple sound sources with two microphones." Journal of the Acoustical Society of America 108, no. 4 (2000): 1888–905. http://dx.doi.org/10.1121/1.1290516.

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Li, Huakang, Jie Huang, Minyi Guo, and Qunfei Zhao. "Spatial Localization of Concurrent Multiple Sound Sources Using Phase Candidate Histogram." Journal of Advanced Computational Intelligence and Intelligent Informatics 15, no. 9 (2011): 1277–86. http://dx.doi.org/10.20965/jaciii.2011.p1277.

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Mobile robots communicating with people would benefit from being able to detect sound sources to help localize interesting events in real-life settings. We propose using a spherical robot with four microphones to determine the spatial locations of multiple sound sources in ordinary rooms. The arrival temporal disparities from phase difference histograms are used to calculate the time differences. A precedence effect model suppresses the influence of echoes in reverberant environments. To integrate spatial cues of different microphones, we map the correlation between different microphone pairs on a 3D map corresponding to the azimuth and elevation of sound source direction. Results of experiments indicate that our proposed system provides sound source distribution very clearly and precisely, even concurrently in reverberant environments with the Echo Avoidance (EA) model.
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Jiang, Bo, XiaoQin Liu, and Xing Wu. "Phase calibration method for microphone array based on multiple sound sources." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 6 (2021): 659–69. http://dx.doi.org/10.3397/in-2021-1620.

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In the microphone array, the phase error of each microphone causes a deviation in sound source localization. At present, there is a lack of effective methods for phase error calibration of the entire microphone array. In order to solve this problem, a phase mismatch calculation method based on multiple sound sources is proposed. This method requires collecting data from multiple sound sources in turn, and constructing a nonlinear equation setthrough the signal delay and the geometric relationship between the microphones and the sound source positions. The phase mismatch of each microphone can be solved from the nonlinear equation set. Taking the single frequency signal as an example, the feasibility of the method is verified by experiments in a semi-anechoic chamber. The phase mismatches are compared with the calibration results of exchanging microphone. The difference of the phase error values measured by the two methods is small. The experiment also shows that the accuracy of sound source localization by beamforming is improved. The method is efficient for phase error calibration of arrays with a large number of microphones.
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Jia, Maoshen, Yuxuan Wu, Changchun Bao, and Jing Wang. "Multiple Sound Sources Localization with Frame-by-Frame Component Removal of Statistically Dominant Source." Sensors 18, no. 11 (2018): 3613. http://dx.doi.org/10.3390/s18113613.

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Multiple sound sources localization is a hot topic in audio signal processing and is widely utilized in many application areas. This paper proposed a multiple sound sources localization method based on a statistically dominant source component removal (SDSCR) algorithm by soundfield microphone. The existence of the statistically weak source (SWS) among soundfield microphone signals is validated by statistical analysis. The SDSCR algorithm with joint an intra-frame and inter-frame statistically dominant source (SDS) discriminations is designed to remove the component of SDS while reserve the SWS component. The degradation of localization accuracy caused by the existence of the SWS is resolved using the SDSCR algorithm. The objective evaluation of the proposed method is conducted in simulated and real environments. The results show that the proposed method achieves a better performance compared with the conventional SSZ-based method both in sources localization and counting.
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Deleforge, Antoine, Florence Forbes, and Radu Horaud. "Acoustic Space Learning for Sound-Source Separation and Localization on Binaural Manifolds." International Journal of Neural Systems 25, no. 01 (2015): 1440003. http://dx.doi.org/10.1142/s0129065714400036.

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In this paper, we address the problems of modeling the acoustic space generated by a full-spectrum sound source and using the learned model for the localization and separation of multiple sources that simultaneously emit sparse-spectrum sounds. We lay theoretical and methodological grounds in order to introduce the binaural manifold paradigm. We perform an in-depth study of the latent low-dimensional structure of the high-dimensional interaural spectral data, based on a corpus recorded with a human-like audiomotor robot head. A nonlinear dimensionality reduction technique is used to show that these data lie on a two-dimensional (2D) smooth manifold parameterized by the motor states of the listener, or equivalently, the sound-source directions. We propose a probabilistic piecewise affine mapping model (PPAM) specifically designed to deal with high-dimensional data exhibiting an intrinsic piecewise linear structure. We derive a closed-form expectation-maximization (EM) procedure for estimating the model parameters, followed by Bayes inversion for obtaining the full posterior density function of a sound-source direction. We extend this solution to deal with missing data and redundancy in real-world spectrograms, and hence for 2D localization of natural sound sources such as speech. We further generalize the model to the challenging case of multiple sound sources and we propose a variational EM framework. The associated algorithm, referred to as variational EM for source separation and localization (VESSL) yields a Bayesian estimation of the 2D locations and time-frequency masks of all the sources. Comparisons of the proposed approach with several existing methods reveal that the combination of acoustic-space learning with Bayesian inference enables our method to outperform state-of-the-art methods.
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ZHU, NA, and SEAN F. WU. "SOUND SOURCE LOCALIZATION IN THREE-DIMENSIONAL SPACE IN REAL TIME WITH REDUNDANCY CHECKS." Journal of Computational Acoustics 20, no. 01 (2012): 1250007. http://dx.doi.org/10.1142/s0218396x12500075.

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Triangulation is commonly used for source localization and most triangulation applications are based on intersection of the bearing direction to locate a source on a two-dimensional plane. In this paper, two new mathematical models (a basic model and an improved one) that expands the traditional triangulation concept to three-dimensional space are developed to locate multiple incoherent sound sources. The basic model uses four microphones and concentrates on solving a set of three quadratic equations simultaneously. The improved model requires more than four microphones and uses the solution from the basic model, as well as analyzing the intersection of bearing angles. Redundancy checks on the time differences of arrival are added to further reduce the source localization error in the improved model. Moreover, the input data are pre-processed and de-noised through filtering and windowing to enhance the effective signal to noise ratio. Various sound sources are tested, including transient, impulsive, continuous, broad-band, and narrow-band sounds. Numerical simulations and experimental validation using the real world sound sources are conducted. The impacts of the source direction/source detection range on the accuracy of source localization results are examined and discussed.
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Tanabe, Ryo, Yoko Sasaki, and Hiroshi Takemura. "Probabilistic 3D Sound Source Mapping System Based on Monte Carlo Localization Using Microphone Array and LIDAR." Journal of Robotics and Mechatronics 29, no. 1 (2017): 94–104. http://dx.doi.org/10.20965/jrm.2017.p0094.

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[abstFig src='/00290001/09.jpg' width='300' text='3D sound source environmental map' ] The study proposes a probabilistic 3D sound source mapping system for a moving sensor unit. A microphone array is used for sound source localization and tracking based on the multiple signal classification (MUSIC) algorithm and a multiple-target tracking algorithm. Laser imaging detection and ranging (LIDAR) is used to generate a 3D geometric map and estimate the location of its six-degrees-of-freedom (6 DoF) using the state-of-the-art gyro-integrated iterative closest point simultaneous localization and mapping (G-ICP SLAM) method. Combining these modules provides sound detection in 3D global space for a moving robot. The sound position is then estimated using Monte Carlo localization from the time series of a tracked sound stream. The results of experiments using the hand-held sensor unit indicate that the method is effective for arbitrary motions of the sensor unit in environments with multiple sound sources.
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Ðurković, Marko, Tim Habigt, Martin Rothbucher, and Klaus Diepold. "Low latency localization of multiple sound sources in reverberant environments." Journal of the Acoustical Society of America 130, no. 6 (2011): EL392—EL398. http://dx.doi.org/10.1121/1.3659146.

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Dissertations / Theses on the topic "Multiple sound sources localization"

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Lombard, Anthony [Verfasser]. "Localization of Multiple Independent Sound Sources in Adverse Environments / Anthony Lombard." München : Verlag Dr. Hut, 2012. http://d-nb.info/1029400148/34.

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Minotto, Vicente Peruffo. "Audiovisual voice activity detection and localization of simultaneous speech sources." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2013. http://hdl.handle.net/10183/77231.

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Em vista da tentência de se criarem intefaces entre humanos e máquinas que cada vez mais permitam meios simples de interação, é natural que sejam realizadas pesquisas em técnicas que procuram simular o meio mais convencional de comunicação que os humanos usam: a fala. No sistema auditivo humano, a voz é automaticamente processada pelo cérebro de modo efetivo e fácil, também comumente auxiliada por informações visuais, como movimentação labial e localizacão dos locutores. Este processamento realizado pelo cérebro inclui dois componentes importantes que a comunicação baseada em fala requere: Detecção de Atividade de Voz (Voice Activity Detection - VAD) e Localização de Fontes Sonoras (Sound Source Localization - SSL). Consequentemente, VAD e SSL também servem como ferramentas mandatórias de pré-processamento em aplicações de Interfaces Humano-Computador (Human Computer Interface - HCI), como no caso de reconhecimento automático de voz e identificação de locutor. Entretanto, VAD e SSL ainda são problemas desafiadores quando se lidando com cenários acústicos realísticos, particularmente na presença de ruído, reverberação e locutores simultâneos. Neste trabalho, são propostas abordagens para tratar tais problemas, para os casos de uma e múltiplas fontes sonoras, através do uso de informações audiovisuais, explorando-se variadas maneiras de se fundir as modalidades de áudio e vídeo. Este trabalho também emprega um arranjo de microfones para o processamento de som, o qual permite que as informações espaciais dos sinais acústicos sejam exploradas através do algoritmo estado-da-arte SRP (Steered Response Power). Por consequência adicional, uma eficiente implementação em GPU do SRP foi desenvolvida, possibilitando processamento em tempo real do algoritmo. Os experimentos realizados mostram uma acurácia média de 95% ao se efetuar VAD de até três locutores simultâneos, e um erro médio de 10cm ao se localizar tais locutores.<br>Given the tendency of creating interfaces between human and machines that increasingly allow simple ways of interaction, it is only natural that research effort is put into techniques that seek to simulate the most conventional mean of communication humans use: the speech. In the human auditory system, voice is automatically processed by the brain in an effortless and effective way, also commonly aided by visual cues, such as mouth movement and location of the speakers. This processing done by the brain includes two important components that speech-based communication require: Voice Activity Detection (VAD) and Sound Source Localization (SSL). Consequently, VAD and SSL also serve as mandatory preprocessing tools for high-end Human Computer Interface (HCI) applications in a computing environment, as the case of automatic speech recognition and speaker identification. However, VAD and SSL are still challenging problems when dealing with realistic acoustic scenarios, particularly in the presence of noise, reverberation and multiple simultaneous speakers. In this work we propose some approaches for tackling these problems using audiovisual information, both for the single source and the competing sources scenario, exploiting distinct ways of fusing the audio and video modalities. Our work also employs a microphone array for the audio processing, which allows the spatial information of the acoustic signals to be explored through the stateof- the art method Steered Response Power (SRP). As an additional consequence, a very fast GPU version of the SRP is developed, so that real-time processing is achieved. Our experiments show an average accuracy of 95% when performing VAD of up to three simultaneous speakers and an average error of 10cm when locating such speakers.
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Khaddour, Hasan. "Lokalizace a interpretace zdrojů zvuku v akustických polich." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-233686.

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Disertační práce se zabývá lokalizací zdrojů zvuku a akustickým zoomem. Hlavním cílem této práce je navrhnout systém s akustickým zoomem, který přiblíží zvuk jednoho mluvčího mezi skupinou mluvčích, a to i když mluví současně. Tento systém je kompatibilní s technikou prostorového zvuku. Hlavní přínosy disertační práce jsou následující: 1. Návrh metody pro odhad více směrů přicházejícího zvuku. 2. Návrh metody pro akustické zoomování pomocí DirAC. 3. Návrh kombinovaného systému pomocí předchozích kroků, který může být použit v telekonferencích.
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Wang, Xipeng. "CONSTANT FALSE ALARM RATE PERFORMANCE OF SOUND SOURCE DETECTION WITH TIME DELAY OF ARRIVAL ALGORITHM." UKnowledge, 2017. http://uknowledge.uky.edu/ece_etds/105.

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Time Delay of Arrival (TDOA) based algorithms and Steered Response Power (SRP) based algorithms are two most commonly used methods for sound source detection and localization. SRP is more robust under high reverberation and multi-target conditions, while TDOA is less computationally intensive. This thesis introduces a modified TDOA algorithm, TDOA delay table search (TDOA-DTS), that has more stable performance than the original TDOA, and requires only 4% of the SRP computation load for a 3-dimensional space of a typical room. A 2-step adaptive thresholding procedure based on a Weibull noise peak distributions for the cross-correlations and a binomial distribution for combing potential peaks over all microphone pairs for the final detection. The first threshold limits the potential target peaks in the microphone pair cross-correlations with a user-defined false-alarm (FA) rates. The initial false-positive peak rate can be set to a higher level than desired for the final FA target rate so that high accuracy is not required of the probability distribution model (where model errors do not impact FA rates as they work for threshold set deep into the tail of the curve). The final FA rate can be lowered to the actual desired value using an M out of N (MON) rule on significant correlation peaks from different microphone pairs associated is a point in the space of interest. The algorithm is tested with simulated and real recorded data to verify resulting FA rates are consistent with the user-defined rates down to 10-6.
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Swartling, Mikael. "Direction of Arrival Estimation and Localization of Multiple Speech Sources in Enclosed Environments." Doctoral thesis, Blekinge Tekniska Högskola, Avdelningen för elektroteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00520.

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Speech communication is gaining in popularity in many different contexts as technology evolves. With the introduction of mobile electronic devices such as cell phones and laptops, and fixed electronic devices such as video and teleconferencing systems, more people are communicating which leads to an increasing demand for new services and better speech quality. Methods to enhance speech recorded by microphones often operate blindly without prior knowledge of the signals. With the addition of multiple microphones to allow for spatial filtering, many blind speech enhancement methods have to operate blindly also in the spatial domain. When attempting to improve the quality of spoken communication it is often necessary to be able to reliably determine the location of the speakers. A dedicated source localization method on top of the speech enhancement methods can assist the speech enhancement method by providing the spatial information about the sources. This thesis addresses the problem of speech-source localization, with a focus on the problem of localization in the presence of multiple concurrent speech sources. The primary work consists of methods to estimate the direction of arrival of multiple concurrent speech sources from an array of sensors and a method to correct the ambiguities when estimating the spatial locations of multiple speech sources from multiple arrays of sensors. The thesis also improves the well-known SRP-based methods with higher-order statistics, and presents an analysis of how the SRP-PHAT performs when the sensor array geometry is not fully calibrated. The thesis is concluded by two envelope-domain-based methods for tonal pattern detection and tonal disturbance detection and cancelation which can be useful to further increase the usability of the proposed localization methods. The main contribution of the thesis is a complete methodology to spatially locate multiple speech sources in enclosed environments. New methods and improvements to the combined solution are presented for the direction-of-arrival estimation, the location estimation and the location ambiguity correction, as well as a sensor array calibration sensitivity analysis.
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Đurković, Marko [Verfasser], Klaus [Akademischer Betreuer] Diepold, and Gordon [Akademischer Betreuer] Cheng. "Localization, Tracking, and Separation of Sound Sources for Cognitive Robots / Marko Đurković. Gutachter: Klaus Diepold ; Gordon Cheng. Betreuer: Klaus Diepold." München : Universitätsbibliothek der TU München, 2012. http://d-nb.info/1031512187/34.

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Wang, Xun. "Sound source localization with data and model uncertainties using the EM and Evidential EM algorithms." Thesis, Compiègne, 2014. http://www.theses.fr/2014COMP2164/document.

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Ce travail de thèse se penche sur le problème de la localisation de sources acoustiques à partir de signaux déterministes et aléatoires mesurés par un réseau de microphones. Le problème est résolu dans un cadre statistique, par estimation via la méthode du maximum de vraisemblance. La pression mesurée par un microphone est interprétée comme étant un mélange de signaux latents émis par les sources. Les positions et les amplitudes des sources acoustiques sont estimées en utilisant l’algorithme espérance-maximisation (EM). Dans cette thèse, deux types d’incertitude sont également pris en compte : les positions des microphones et le nombre d’onde sont supposés mal connus. Ces incertitudes sont transposées aux données dans le cadre théorique des fonctions de croyance. Ensuite, les positions et les amplitudes des sources acoustiques peuvent être estimées en utilisant l’algorithme E2M, qui est une variante de l’algorithme EM pour les données incertaines.La première partie des travaux considère le modèle de signal déterministe sans prise en compte de l’incertitude. L’algorithme EM est utilisé pour estimer les positions et les amplitudes des sources. En outre, les résultats expérimentaux sont présentés et comparés avec le beamforming et la holographie optimisée statistiquement en champ proche (SONAH), ce qui démontre l’avantage de l’algorithme EM. La deuxième partie considère le problème de l’incertitude du modèle et montre comment les incertitudes sur les positions des microphones et le nombre d’onde peuvent être quantifiées sur les données. Dans ce cas, la fonction de vraisemblance est étendue aux données incertaines. Ensuite, l’algorithme E2M est utilisé pour estimer les sources acoustiques. Finalement, les expériences réalisées sur les données réelles et simulées montrent que les algorithmes EM et E2M donnent des résultats similaires lorsque les données sont certaines, mais que ce dernier est plus robuste en présence d’incertitudes sur les paramètres du modèle. La troisième partie des travaux présente le cas de signaux aléatoires, dont l’amplitude est considérée comme une variable aléatoire gaussienne. Dans le modèle sans incertitude, l’algorithme EM est utilisé pour estimer les sources acoustiques. Dans le modèle incertain, les incertitudes sur les positions des microphones et le nombre d’onde sont transposées aux données comme dans la deuxième partie. Enfin, les positions et les variances des amplitudes aléatoires des sources acoustiques sont estimées en utilisant l’algorithme E2M. Les résultats montrent ici encore l’avantage d’utiliser un modèle statistique pour estimer les sources en présence, et l’intérêt de prendre en compte l’incertitude sur les paramètres du modèle<br>This work addresses the problem of multiple sound source localization for both deterministic and random signals measured by an array of microphones. The problem is solved in a statistical framework via maximum likelihood. The pressure measured by a microphone is interpreted as a mixture of latent signals emitted by the sources; then, both the sound source locations and strengths can be estimated using an expectation-maximization (EM) algorithm. In this thesis, two kinds of uncertainties are also considered: on the microphone locations and on the wave number. These uncertainties are transposed to the data in the belief functions framework. Then, the source locations and strengths can be estimated using a variant of the EM algorithm, known as Evidential EM (E2M) algorithm. The first part of this work begins with the deterministic signal model without consideration of uncertainty. The EM algorithm is then used to estimate the source locations and strengths : the update equations for the model parameters are provided. Furthermore, experimental results are presented and compared with the beamforming and the statistically optimized near-field holography (SONAH), which demonstrates the advantage of the EM algorithm. The second part raises the issue of model uncertainty and shows how the uncertainties on microphone locations and wave number can be taken into account at the data level. In this case, the notion of the likelihood is extended to the uncertain data. Then, the E2M algorithm is used to solve the sound source estimation problem. In both the simulation and real experiment, the E2M algorithm proves to be more robust in the presence of model and data uncertainty. The third part of this work considers the case of random signals, in which the amplitude is modeled by a Gaussian random variable. Both the certain and uncertain cases are investigated. In the former case, the EM algorithm is employed to estimate the sound sources. In the latter case, microphone location and wave number uncertainties are quantified similarly to the second part of the thesis. Finally, the source locations and the variance of the random amplitudes are estimated using the E2M algorithm
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Fischer, Jeoffrey. "Identification de sources aéroacoustiques au voisinage de corps non profilés par formation de voies fréquentielle et temporelle." Thesis, Poitiers, 2014. http://theses.univ-poitiers.fr/62768/2014-Fischer-Jeoffrey-These.

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La localisation de sources aéroacoustiques sur les corps automobiles est actuellement un sujet d’intérêt majeur pour les industriels. Le traitement d’antenne microphonique par formation de voies (beamforming) est une méthode robuste, classiquement utilisée dans ce cadre. L’objectif principal de ce manuscrit concerne ainsi la détection de sources aéroacoustiques sur des corps non profilés. Deux configurations expérimentales sont envisagées : une marche montante qui représente un cas académique, et un corps tridimensionnel générant des structures tourbillonnaires de type montant de baie se rapprochant du cadre de l’industrie automobile. La localisation de sources par formation de voies classique a permis d’identifier, pour différentes gammes de fréquence, les principales régions d’émission acoustique, à savoir : les zones tourbillonnaires amont et aval sur la marche et les montants de baie latéraux sur le corps tridimensionnel. De plus, des tendances similaires dans les mesures de pression pariétale fluctuante et de pression acoustique en champ lointain ont été observées. L’étude s’est ensuite dirigée vers la détection d’intermittences acoustiques afin de déterminer dans quelle mesure, à l’instar du bruit de jet, le bruit d’écoulement en présence d’obstacle présente un caractère intermittent. Un processus de seuillage sur le champ lointain mesuré a permis de sélectionner des événements représentant 80% de l’énergie du signal original et 20% de sa durée sur les deux configurations. Une méthode de formation de voies temporelle, en lien direct avec la technique de retournement temporel, a été développée afin de réaliser une imagerie de sources aéroacoustiques en fonction du temps.L’utilisation de cette technique permet de montrer que les événements sélectionnés à partir du seuillage correspondent à des sources intermittentes dont on peut déterminer les lieux et les instants d’émission (obéissant à une distribution statistique Gamma). Le bruit aéroacoustique généré par les corps non profilés considérés dans cette étude peut donc être vu comme une succession d’événements intermittents identifiables. Enfin, la reconstruction des signaux acoustiques à partir d’une famille d’ondelettes a été effectué. Les spectres du signal original et filtré sont fortement semblables, une différence de l’ordre de 10% ayant été observée entre eux pour les deux maquettes, confirmant l’importance des événements intermittents dans le rayonnement aéroacoustique des corps non profilés<br>The localization of aeroacoustic sources of automotive bodies is currently a topic of major interest to industry. Beamforming is a robust method typically used in this context. The main objective of this thesis relates to the detection of aeroacoustic sources on bluff bodies. Two experimental configurations are considered : a forwardfacing step that is an academic event, and a three dimensional bluff body generating A-pillar vortices approaching the automotive industry. Source localization through classical beamforming has enabled to detect the main regions of acoustic emission for different frequency ranges, namely : upstream and downstream vortices around thestep and A-pillar vortices generated on both sides of the 3D bluff body. In addition, relationships have been observed between wall pressure fluctuations and acoustic field radiated. The study was then directed to the detection of intermittent acoustic events to determine whether, like jet noise, the noise radiated by an obstacle in the flow is composed of intermittent signatures. A thresholding process on the far field measurements was used to select events representing 80% of the energy of the original signal and 20% of its time for both configurations. A time-domain beamforming algorithm, directly linked to the time reversal technique, has been developed to achieve a spatio-temporal information about the intermittent noise sources. The use of this technique has proved that the events selected with the tresholding technique correspond to intermittent acoustic sources which space and time informations canbe determined (they follow a Gamma distribution). The aeroacoustic noise radiated by the bluff bodies considered in this study can therefore be seen as a succession of intermittent events that can be identified. Finally, the reconstruction of intermittent acoustic signals using a family of wavelets was performed. The Fourier spectra of the original and reconstructed signals are highly similar, a difference of about 10% was observed, confirming the importance of intermittent events in the noise radiated by bluff bodies
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Carlo, Diego Di. "Echo-aware signal processing for audio scene analysis." Thesis, Rennes 1, 2020. http://www.theses.fr/2020REN1S075.

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La plupart des méthodes de traitement du signal audio considèrent la réverbération et en particulier les échos acoustiques comme une nuisance. Cependant, ceux-ci transmettent des informations spatiales et sémantiques importantes sur les sources sonores et des méthodes essayant de les prendre en compte ont donc récemment émergé.. Dans ce travail, nous nous concentrons sur deux directions. Tout d’abord, nous étudions la manière d’estimer les échos acoustiques à l’aveugle à partir d’enregistrements microphoniques. Deux approches sont proposées, l’une s’appuyant sur le cadre des dictionnaires continus, l’autre sur des techniques récentes d’apprentissage profond. Ensuite, nous nous concentrons sur l’extension de méthodes existantes d’analyse de scènes audio à leurs formes sensibles à l’écho. Le cadre NMF multicanal pour la séparation de sources audio, la méthode de localisation SRP-PHAT et le formateur de voies MVDR pour l’amélioration de la parole sont tous étendus pour prendre en compte les échos. Ces applications montrent comment un simple modèle d’écho peut conduire à une amélioration des performances<br>Most of audio signal processing methods regard reverberation and in particular acoustic echoes as a nuisance. However, they convey important spatial and semantic information about sound sources and, based on this, recent echo-aware methods have been proposed. In this work we focus on two directions. First, we study the how to estimate acoustic echoes blindly from microphone recordings. Two approaches are proposed, one leveraging on continuous dictionaries, one using recent deep learning techniques. Then, we focus on extending existing methods in audio scene analysis to their echo-aware forms. The Multichannel NMF framework for audio source separation, the SRP-PHAT localization method, and the MVDR beamformer for speech enhancement are all extended to their echo-aware versions
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Aloui, Nadia. "Localisation sonore par retournement temporel." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENT079/document.

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L'objectif général de cette thèse était de proposer une solution de localisation en intérieur à la fois simple et capable de surmonter les défis de la propagation dans les environnements en intérieur. Pour ce faire, un système de localisation basé sur la méthode des signatures et adoptant le temps d'arrivée du signal de l'émetteur au récepteur comme signature, a été proposé. Le système présente deux architectures différentes, une première orientée privée utilisant la méthode d'accès multiple à répartition par code et une deuxième centralisée basée sur la méthode d'accès multiple à répartition dans le temps. Le système calcule la position de l'objet d'intérêt par la méthode de noyau. Une comparaison expérimentale entre le système à architecture orientée privée et un système de localisation sonore déjà existant et basé sur la méthode de trilatération, a permis de confirmer les résultats trouvés dans le cas de la localisation par ondes radiofréquences. Cependant, nos expérimentations étaient les premières à montrer l'effet de la réverbération sur les approches de la localisation acoustique. Dans un second lieu, un système de localisation basé sur la technique de retournement temporel, permettant une localisation simultanée de sources avec différentes précisions, a été testé par simulations en faisant varier le nombre de sources. Ce système a été ensuite validé par expérimentations. Dans la dernière partie de notre étude, nous nous sommes intéressés à la réduction de l'audibilité du signal utile à la localisation par recours à la psycho-acoustique. Un filtre défini à partir du seuil d'audition absolu a été appliqué au signal de localisation. Nos résultats ont montré une amélioration de la précision de localisation comparé au système de localisation sans modèle psycho-acoustique et ce grâce à l'utilisation d'un filtre adapté au modèle psycho-acoustique à la réception. Par ailleurs, l'écoute du signal après application du modèle psycho-acoustique a montré une réduction significative de son audibilité comparée à celle du signal original<br>The objective of this PhD is to propose a location solution that should be simple and robust to multipath that characterizes the indoor environments. First, a location system that exploits the time domain of channel parameters has been proposed. The system adopts the time of arrival of the path of maximum amplitude as a signature and estimates the target position through nonparametric kernel regression. The system was evaluated in experiments for two main configurations: a privacy-oriented configuration with code-division multiple-access operation and a centralized configuration with time-division multiple-access operation. A comparison between our privacy-oriented system and another acoustic location system based on code-division multiple-access operation and lateration method confirms the results found in radiofrequency-based localization. However, our experiments are the first to demonstrate the detrimental effect that reverberation has on acoustic localization approaches. Second, a location system based on time reversal technique and able to localize simultaneously sources with different location precisions has been tested through simulations for different values of the number of sources. The system has then been validated by experiments. Finally, we have been interested in reducing the audibility of the localization signal through psycho-acoustics. A filter, set from the absolute threshold of hearing, is then applied to the signal. Our results showed an improvement in precision, when compared to the location system without psychoacoustic model, thanks to the use of matched filter at the receiver. Moreover, we have noticed a significant reduction in the audibility of the filtered signal compared to that of the original signal
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Books on the topic "Multiple sound sources localization"

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Luxon, Linda. Disorders of hearing. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780198569381.003.0301.

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Hearing loss is the commonest sensory disability worldwide, and the World Health Organisation has estimated that 278 million people suffer a moderate to profound hearing loss in both ears, with 80 per cent of deaf and hearing-impaired people living in low- and middle-income countries (WHO 2006). Tinnitus affects approximately 10 per cent of developed populations (Coles 1984) and of these, 5 per cent find the symptom troublesome and seek help (Davis 1995). Tinnitus and hearing loss are primary symptoms of disordered cochlear function, but may also present as a result of central auditory pathology with normal cochlear function. Pathology affecting the central auditory pathways characteristically presents as difficulty hearing in conditions of poor signal-to-noise ratio, for example, in a classroom in the presence of background noise, listening to transmitted sound, for example on the telephone or on a television, and sound localization. As a consequence of multiple relays and bilateral representation above the level of the cochlear nuclei, central auditory dysfunction does not present with hearing loss. Hearing loss and/or tinnitus, with or without associated vestibular abnormalities, will most commonly be the result of otological pathology. However, importantly for the neurologist cochlear, VIII nerve, or central auditory dysfunction may be part of the clinical presentation of a neurological disorder.
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Book chapters on the topic "Multiple sound sources localization"

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Qian, Rui, Di Hu, Heinrich Dinkel, Mengyue Wu, Ning Xu, and Weiyao Lin. "Multiple Sound Sources Localization from Coarse to Fine." In Computer Vision – ECCV 2020. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58565-5_18.

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Kotus, Józef. "Multiple Sound Sources Localization in Real Time Using Acoustic Vector Sensor." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30721-8_17.

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Nakashima, Taichi, Kazunori Komatani, and Satoshi Sato. "Integration of Multiple Sound Source Localization Results for Speaker Identification in Multiparty Dialogue System." In Natural Interaction with Robots, Knowbots and Smartphones. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8280-2_14.

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Dhillon, Ramindar S., and James W. Fairley. "Localization of sound stimulus." In Multiple-choice Questions in Otolaryngology. Palgrave Macmillan UK, 1989. http://dx.doi.org/10.1007/978-1-349-10805-3_37.

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Pfeifer, Christian, Jonas P. Moeck, C. Oliver Paschereit, and Lars Enghardt. "Localization of Sound Sources in Combustion Chambers." In Combustion Noise. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02038-4_10.

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Dey, Nilanjan, and Amira S. Ashour. "Sources Localization and DOAE Techniques of Moving Multiple Sources." In SpringerBriefs in Electrical and Computer Engineering. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-73059-2_3.

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Lemke, Mathias, and Lewin Stein. "Adjoint-Based Identification of Sound Sources for Sound Reinforcement and Source Localization." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52429-6_17.

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Maier, Christian, Wolfram Pannert, and Winfried Waidmann. "Localization of Rotating Sound Sources Using Time Domain Beamforming Code." In Advanced Structured Materials. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00506-5_10.

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Maier, Christian, Wolfram Pannert, and Winfried Waidmann. "Localization of Rotating Sound Sources Using Time Domain Beamforming Code." In Advanced Structured Materials. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02836-1_4.

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Krolikowski, Rafal, Andrzej Czyzewski, and Bozena Kostek. "Localization of Sound Sources by Means of Recurrent Neural Networks." In Rough Sets and Current Trends in Computing. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45554-x_76.

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Conference papers on the topic "Multiple sound sources localization"

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Li, Huakang, Akira Saji, Keita Tanno, Jun Ma, Jie Huang, and Qunfei Zhao. "Spatial localization of concurrent multiple sound sources." In 2010 2nd International Symposium on Aware Computing (ISAC). IEEE, 2010. http://dx.doi.org/10.1109/isac.2010.5670458.

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Gao, Shang, Maoshen Jia, Yuxuan Wu, Yitian Jia, and Mingchen Wei. "Multiple Sound Sources Localization by using Statistical Source Component Equalization." In ICCPR '19: 2019 8th International Conference on Computing and Pattern Recognition. ACM, 2019. http://dx.doi.org/10.1145/3373509.3373582.

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Quang Nguyen and JongSuk Choi. "Multiple sound sources localization with perception sensor network." In 2013 IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). IEEE, 2013. http://dx.doi.org/10.1109/roman.2013.6628515.

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Rothbucher, Martin, Marko Durkovic, Tim Habigt, Hao Shen, and Klaus Diepold. "HRTF-based localization and separation of multiple sound sources." In 2012 RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication. IEEE, 2012. http://dx.doi.org/10.1109/roman.2012.6343894.

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Moing, Guillaume Le, Phongtharin Vinayavekhin, Tadanobu Inoue, et al. "Learning Multiple Sound Source 2D Localization." In 2019 IEEE 21st International Workshop on Multimedia Signal Processing (MMSP). IEEE, 2019. http://dx.doi.org/10.1109/mmsp.2019.8901685.

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Keyrouz, Fakheredine. "Robotic Binaural Localization and Separation of Multiple Simultaneous Sound Sources." In 2017 IEEE 11th International Conference on Semantic Computing (ICSC). IEEE, 2017. http://dx.doi.org/10.1109/icsc.2017.18.

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Nogueira, Luiz C. F., and Mariane R. Petraglia. "Robust localization of multiple sound sources based on BSS algorithms." In 2015 IEEE 24th International Symposium on Industrial Electronics (ISIE). IEEE, 2015. http://dx.doi.org/10.1109/isie.2015.7281532.

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Gao, Shan, Yankun Huang, Tao Zhang, Xihong Wu, and Tianshu Qu. "A Modified Frequency Weighted MUSIC Algorithm for Multiple Sound Sources Localization." In 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP). IEEE, 2018. http://dx.doi.org/10.1109/icdsp.2018.8631636.

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Grondin, François, and James Glass. "Multiple Sound Source Localization with SVD-PHAT." In Interspeech 2019. ISCA, 2019. http://dx.doi.org/10.21437/interspeech.2019-2653.

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Huang, Jie, Noboru Onishi, and Noboru Sugie. "A System for Multiple Sound Source Localization." In 5th International Symposium on Automation and Robotics in Construction. International Association for Automation and Robotics in Construction (IAARC), 1988. http://dx.doi.org/10.22260/isarc1988/0040.

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Reports on the topic "Multiple sound sources localization"

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Frazer, L. N., and Eva-Marie Nosal. Passive Localization of Multiple Sources Using Widely-Spaced Arrays With Application to Marine Mammals. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada613674.

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Frazer, L. N., and Eva-Marie Nosal. Passive Localization of Multiple Sources Using Widely-Spaced Arrays with Application to Marine Mammals. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada573282.

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Kamrath, Matthew, Vladimir Ostashev, D. Wilson, Michael White, Carl Hart, and Anthony Finn. Vertical and slanted sound propagation in the near-ground atmosphere : amplitude and phase fluctuations. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40680.

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Sound propagation along vertical and slanted paths through the near-ground atmosphere impacts detection and localization of low-altitude sound sources, such as small unmanned aerial vehicles, from ground-based microphone arrays. This article experimentally investigates the amplitude and phase fluctuations of acoustic signals propagating along such paths. The experiment involved nine microphones on three horizontal booms mounted at different heights to a 135-m meteorological tower at the National Wind Technology Center (Boulder, CO). A ground-based loudspeaker was placed at the base of the tower for vertical propagation or 56m from the base of the tower for slanted propagation. Phasor scatterplots qualitatively characterize the amplitude and phase fluctuations of the received signals during different meteorological regimes. The measurements are also compared to a theory describing the log-amplitude and phase variances based on the spectrum of shear and buoyancy driven turbulence near the ground. Generally, the theory correctly predicts the measured log-amplitude variances, which are affected primarily by small-scale, isotropic turbulent eddies. However, the theory overpredicts the measured phase variances, which are affected primarily by large-scale, anisotropic, buoyantly driven eddies. Ground blocking of these large eddies likely explains the overprediction.
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