Relevant bibliographies by topics / Microphone arrays

Academic literature on the topic 'Microphone arrays'

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Published: 4 June 2021
Last updated: 8 June 2024

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Journal articles on the topic "Microphone arrays"

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Mittal, Manan, Kanad Sarkar, Austin Lu, Ryan M. Corey, and Andrew C. Singer. "Source separation using bandlimited external microphones and a microphone array." Journal of the Acoustical Society of America 153, no. 3_supplement (March 1, 2023): A52. http://dx.doi.org/10.1121/10.0018131.

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Modern listening devices are equipped with air-conducted microphones and contact microphones. External microphones, like those on a listening device, have been used to estimate relative transfer functions (RTFs) at microphone arrays. With numerous active sound sources, the air-conducted microphones perform poorly while the contact microphones are robust to external noise. A drawback of contact microphones is that they are bandlimited. Past work has shown that the contact microphone and microphone array can be combined to estimate RTFs in the low frequencies. To overcome the limitations of the contact microphone, we propose a method that leverages the full-band signal at the microphone array to provide beamforming gains at higher frequencies. We demonstrate this method by separating three human talkers in a noisy environment.
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Sakavičius, Saulius. "DATASET FOR EVALUATION OF THE PERFORMANCE OF THE METHODS OF SOUND SOURCE LOCALIZATION ALGORITHMS USING TETRAHEDRAL MICROPHONE ARRAYS." Mokslas - Lietuvos ateitis 12 (February 24, 2020): 1–8. http://dx.doi.org/10.3846/mla.2020.11462.

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For the development and evaluation of a sound source localization and separation methods, a concise audio dataset with complete geometrical information about the room, the positions of the sound sources, and the array of microphones is needed. Computer simulation of such audio and geometrical data often relies on simplifications and are sufficiently accurate only for a specific set of conditions. It is generally desired to evaluate algorithms on real-world data. For a three-dimensional sound source localization or direction of arrival estimation, a non-coplanar microphone array is needed.Simplest and most general type of non-coplanar array is a tetrahedral array. There is a lack of openly accessible realworld audio datasets obtained using such arrays. We present an audio dataset for the evaluation of sound source localization algorithms, which involve tetrahedral microphone arrays. The dataset is complete with the geometrical information of the room, the positions of the sound sources and the microphone array. Array audio data was captured for two tetrahedral microphone arrays with different distances between microphones and one or two active sound sources. The dataset is suitable for speech recognition and direction-of-arrival estimation, as the signals used for sound sources were speech signals.
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Segers, Laurent, Jurgen Vandendriessche, Thibaut Vandervelden, Benjamin Johan Lapauw, Bruno da Silva, An Braeken, and Abdellah Touhafi. "CABE: A Cloud-Based Acoustic Beamforming Emulator for FPGA-Based Sound Source Localization." Sensors 19, no. 18 (September 10, 2019): 3906. http://dx.doi.org/10.3390/s19183906.

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Microphone arrays are gaining in popularity thanks to the availability of low-cost microphones. Applications including sonar, binaural hearing aid devices, acoustic indoor localization techniques and speech recognition are proposed by several research groups and companies. In most of the available implementations, the microphones utilized are assumed to offer an ideal response in a given frequency domain. Several toolboxes and software can be used to obtain a theoretical response of a microphone array with a given beamforming algorithm. However, a tool facilitating the design of a microphone array taking into account the non-ideal characteristics could not be found. Moreover, generating packages facilitating the implementation on Field Programmable Gate Arrays has, to our knowledge, not been carried out yet. Visualizing the responses in 2D and 3D also poses an engineering challenge. To alleviate these shortcomings, a scalable Cloud-based Acoustic Beamforming Emulator (CABE) is proposed. The non-ideal characteristics of microphones are considered during the computations and results are validated with acoustic data captured from microphones. It is also possible to generate hardware description language packages containing delay tables facilitating the implementation of Delay-and-Sum beamformers in embedded hardware. Truncation error analysis can also be carried out for fixed-point signal processing. The effects of disabling a given group of microphones within the microphone array can also be calculated. Results and packages can be visualized with a dedicated client application. Users can create and configure several parameters of an emulation, including sound source placement, the shape of the microphone array and the required signal processing flow. Depending on the user configuration, 2D and 3D graphs showing the beamforming results, waterfall diagrams and performance metrics can be generated by the client application. The emulations are also validated with captured data from existing microphone arrays.
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Mittal, Manan, Kanad Sarkar, Ryan M. Corey, and Andrew C. Singer. "Group conversation enhancement using distributed microphone arrays with adaptive binauralization." Journal of the Acoustical Society of America 152, no. 4 (October 2022): A143. http://dx.doi.org/10.1121/10.0015831.

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Hearing aids and other listening devices perform poorly in noisy, reverberant venues like restaurants and conference centers with numerous active sound sources. Microphone arrays can use array processing techniques like beamforming to isolate talkers from a specific region in the room while attenuating undesired sound sources. However, beamforming often removes spatial cues and is typically restricted to isolating a single talker at a time. Previous work has shown the effectiveness of remote microphones worn by talkers and adapting the signal at the earpiece to improve the intelligibility of group conversations. Due to the increase in hybrid meetings and classrooms, many spaces are equipped with high throughput, low latency devices including large microphone arrays. In this work, we present a system that aggregates information collected by microphone arrays distributed in a room to enhance the intelligibility of talkers in a group conversation. The beamformed signal from the microphone arrays is adapted to match the magnitude and phase of the earpiece microphones. The filters are continuously updated in order to track motion of both the listeners and talkers.
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West, James E., Ian M. McLane, and Valerie Rennoll. "Sixty years of contributions to the world of microphones." Journal of the Acoustical Society of America 153, no. 3_supplement (March 1, 2023): A106. http://dx.doi.org/10.1121/10.0018320.

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For almost 60 years, electret microphones have been the preferred sensors for applications in communications, mainly because the microphones are linear over a broad frequency range and rather simple to manufacture. Because the electret microphone can be mass produced with only slight differences in phase and frequency response, multiple units can be combined to form a variety of directional arrays ranging from second-order unidirectional to two-dimensional arrays for focusing on a specific area. While electret microphones and arrays have similar utility for monitoring lung and heart sounds from the body, the body sounds captured can be easily corrupted by noise external to the body. Advanced signal processing techniques can mitigate contributions from airborne noise but are computationally intensive. By modifying the acoustic impedance of the electret microphone’s diaphragm to match that of the body, we are able to capture high-fidelity heart and lung sounds without corruption from airborne noise. This redesign of the original electret microphone could provide a method to continuously monitor lung and heart sounds from a subject regardless of their surrounding noise environment.
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Peral-Orts, Ramón, Emilio Velasco-Sánchez, Nuria Campillo-Davó, and Héctor Campello-Vicente. "Technical Notes: Using Microphone Arrays to Detect Moving Vehicle Velocity." Archives of Acoustics 38, no. 3 (September 1, 2013): 407–15. http://dx.doi.org/10.2478/aoa-2013-0048.

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Abstract The noise of motor vehicles is one of the most important problems as regards to pollution on main roads. However, this unpleasant characteristic could be used to determine vehicle speed by external observers. Building on this idea, the present study investigates the capabilities of a microphone array system to identify the position and velocity of a vehicle travelling on a previously established route. Such linear microphone array has been formed by a reduced number of microphones working at medium frequencies as compared to industrial microphone arrays built for location purposes, and operates with a processing algorithm that ultimately identifies the noise source location and reduces the error in velocity estimation
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Chung, Ming-An, Hung-Chi Chou, and Chia-Wei Lin. "Sound Localization Based on Acoustic Source Using Multiple Microphone Array in an Indoor Environment." Electronics 11, no. 6 (March 12, 2022): 890. http://dx.doi.org/10.3390/electronics11060890.

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Sound signals have been widely applied in various fields. One of the popular applications is sound localization, where the location and direction of a sound source are determined by analyzing the sound signal. In this study, two microphone linear arrays were used to locate the sound source in an indoor environment. The TDOA is also designed to deal with the problem of delay in the reception of sound signals from two microphone arrays by using the generalized cross-correlation algorithm to calculate the TDOA. The proposed microphone array system with the algorithm can successfully estimate the sound source’s location. The test was performed in a standardized chamber. This experiment used two microphone arrays, each with two microphones. The experimental results prove that the proposed method can detect the sound source and obtain good performance with a position error of about 2.0~2.3 cm and angle error of about 0.74 degrees. Therefore, the experimental results demonstrate the feasibility of the system.
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Ershov, Victor, and Vadim Palchikovskiy. "DESIGNING PLANAR MICROPHONE ARRAY FOR SOUND SOURCE LOCALIZATION." Akustika 32 (March 1, 2019): 123–29. http://dx.doi.org/10.36336/akustika201932123.

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Mathematical background for designing planar microphone array for localization of sound sources are described shortly. The designing is based on optimization of objective function, which is maximum dynamic range of sound source localization. The design parameters are radial coordinates (distance along the beam from the center of the array) and angle coordinates (beam inclination) of the microphones. It is considered the arrays with the same radial coordinates of the microphones for each beam and the independent radial coordinates of each microphone, as well as the same inclination angle for all beams and the individual inclination angle of each beam. As constraints, it is used the minimum allowable distance between two adjacent microphones, and minimum and maximum diameter of the working area of the array. The solution of the optimization problem is performed by the Minimax method. An estimation of the resolution quality of designed arrays was carried out based on localization of three monopole sources. The array of 3 m in diameter without inclination of the beams and with different radial coordinates of the microphones on each beam was found to be the most efficient configuration among the considered ones.
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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 (August 1, 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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Luo, Xueqin, Xudong Zhao, Gongping Huang, Jilu Jin, Jingdong Chen, and Jacob Benesty. "Design of fully steerable broadband beamformers with concentric circular superarrays." Journal of the Acoustical Society of America 154, no. 4 (October 1, 2023): 1996–2009. http://dx.doi.org/10.1121/10.0021164.

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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-dimensional space, the performance of those arrays would suffer from significant degradation if the sound sources are out of the sensors' plane, which happens due to the incomplete spatial sampling of the sound field. This paper addresses this issue by presenting a new method to design concentric circular microphone arrays using both omnidirectional microphones and bidirectional microphones (directional sensors with dipole-shaped patterns). Such arrays are referred to as superarrays as they are able to achieve higher array gain as compared to their traditional counterparts with omnidirectional sensors. It is shown that, with the use of bidirectional microphones, the spatial harmonic components that are missing in the traditional arrays are compensated back. A beamforming method is then presented to design beamformers that can achieve frequency-invariant beampatterns with high directivity and are fully steerable in the three-dimensional space. Simulations and real experiments validate the effectiveness and good properties of the presented method.
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Dissertations / Theses on the topic "Microphone arrays"

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Gillett, Philip Winslow. "Head Mounted Microphone Arrays." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/28867.

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Microphone arrays are becoming increasingly integrated into every facet of life. From sonar to gunshot detection systems to hearing aids, the performance of each system is enhanced when multi-sensor processing is implemented in lieu of single sensor processing. Head mounted microphone arrays have a broad spectrum of uses that follow the rigorous demands of human hearing. From noise cancellation to focused listening, from localization to classification of sound sources, any and all attributes of human hearing may be augmented through the use of microphone arrays and signal processing algorithms. Placing a set of headphones on a human provides several desirable features such as hearing protection, control over the acoustic environment (via headphone speakers), and a means of communication. The shortcoming of headphones is the complete occlusion of the pinnae (the ears), disrupting auditory cues utilized by humans for sound localization. This thesis presents the underlying theory in designing microphone arrays placed on diffracting bodies, specifically the human head. A progression from simple to complex geometries chronicles the effect of diffracting structures on array manifold matrices. Experimental results validate theoretical and computational models showing that arrays mounted on diffracting structures provide better beamforming and localization performance than arrays mounted in the free field. Data independent, statistically optimal, and adaptive beamforming methods are presented to cover a broad range of goals present in array applications. A framework is developed to determine the performance potential of microphone array designs regardless of geometric complexity. Directivity index, white noise gain, and singular value decomposition are all utilized as performance metrics for array comparisons. The biological basis for human hearing is presented as a fundamental attribute of headset array optimization methods. A method for optimizing microphone locations for the purpose of the recreation of HRTFs is presented, allowing transparent hearing (also called natural hearing restoration) to be performed. Results of psychoacoustic testing with a prototype headset array are presented and examined. Subjective testing shows statistically significant improvements over occluded localization when equipped with this new transparent hearing system prototype.
Ph. D.
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Barnes, Hugh. "Speech enhancement using microphone arrays." Thesis, Imperial College London, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.409581.

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Lustberg, Robert Jack. "Acoustic beamforming using microphone arrays." Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/12338.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1993.
Includes bibliographical references (leaves 71-72).
by Robert Jack Lustberg.
M.S.
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Mošner, Ladislav. "Microphone Arrays for Speaker Recognition." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2017. http://www.nusl.cz/ntk/nusl-363803.

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Tato diplomová práce se zabývá problematikou vzdáleného rozpoznávání mluvčích. V případě dat zachycených odlehlým mikrofonem se přesnost standardního rozpoznávání značně snižuje, proto jsem navrhl dva přístupy pro zlepšení výsledků. Prvním z nich je použití mikrofonního pole (záměrně rozestavené sady mikrofonů), které je schopné nasměrovat virtuální "paprsek" na pozici řečníka. Dále jsem prováděl adaptaci komponent systému (PLDA skórování a extraktoru i-vektorů). S využitím simulace pokojových podmínek jsem syntetizoval trénovací a testovací data ze standardní datové sady NIST 2010. Ukázal jsem, že obě techniky a jejich kombinace vedou k výraznému zlepšení výsledků. Dále jsem se zabýval společným určením identity a pozice mluvčího. Zatímco výsledky ve venkovním simulovaném prostředí (bez ozvěn) jsou slibné, výsledky z interiéru (s ozvěnami) jsou smíšené a vyžadují další prozkoumání. Na závěr jsem mohl systémem vyhodnotit omezené množství reálných dat získaných přehráním a záznamem nahrávek ve skutečné místnosti. Zatímco výsledky pro mužské nahrávky odpovídají simulaci, výsledky pro ženské nahrávky nejsou přesvědčivé a vyžadují další analýzu.
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Moore, Darren C. "Speech enhancement using microphone arrays." Thesis, Queensland University of Technology, 2000. https://eprints.qut.edu.au/36141/1/36141_Moore_2000.pdf.

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This thesis presents a comparative analysis of baseline microphone array speech enhancement techniques that are prominent in current literature. Delay-sum beamforming, sub-array beamforming, near- and far-field superdirectivity, the generalised sidelobe canceller and the adaptive system for microphone-array noise reduction (AivINOR) are evaluated in varying noise conditions and for different array geometries. The effect of complementing each technique with a postfilter is also assessed. A novel beamformer, termed the near-field adaptive beamformer (NFAB), is introduced and then shown to provide superior enhancement performance over any of the baseline techniques assessed. A description of the design and implementation of a high-speed, multi-channel speech data acquisition system is also presented.
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Ryan, James G. "Near-field beamforming using microphone arrays." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0015/NQ48335.pdf.

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Goh, Boon Aik. "Adaptive subband beamforming for microphone arrays." Thesis, University of Leeds, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.424021.

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Cardoso, Clara Ferreira. "Signal processing for circular microphone arrays." Thesis, University of Southampton, 2007. https://eprints.soton.ac.uk/421465/.

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McCowan, Iain A. "Robust speech recognition using microphone arrays." Thesis, Queensland University of Technology, 2001.

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The performance of state-of-the-art automatic speech recognition has recently attained levels sufficient for deployment in practical applications. As speech recognition technology undergoes the transition from research laboratories to the consumer market, much work remains to be done in the research domain in order to produce recognition systems that will perform well in practical configurations and realistic noise conditions. A major problem facing speech recognition researchers is the presence of undesired noise in the input speech signal. Systems that provide high performance levels in clean laboratory conditions often degrade dramatically in more realistic noise conditions. A varying level of noise exists in the majority of speech recognition applications, whether it be conflicting speech and computer noise in an office, engine and wind noise in vehicles, machine noise in factories, or any other source of undesired sound. For a speech recognition system to be practical, it must be robust to a variety of noisy conditions. As well as the problem of noise reduction, another issue in many applications of speech recognition is the desire for hands-free acquisition of the speech signal. Currently, most speech recognition systems require a close-talking head-set microphone to provide the input speech signal, as the performance degrades markedly when a distant microphone is used. An emerging topic of research is the use of microphone arrays in speech processing applications. A microphone array consists of multiple microphones placed at different spatial locations. Built upon a knowledge of sound propagation principles, the multiple inputs can be manipulated to enhance or attenuate signals emanating from particular directions. In this way, microphone arrays provide a means of enhancing a desired signal in the presence of corrupting noise sources. Moreover, this enhancement is based purely on knowledge of the source location, and so microphone array techniques are applicable to a wide variety of noise types. This thesis investigates the use of microphone arrays to improve the robustness of hands-free speech recognition systems in noisy conditions. Microphone arrays have great potential in practical applications of speech recognition, due to their ability to provide both noise robustness and hands-free signal acquisition. As well as investigating the use of microphone arrays as a speech enhancement stage prior to recognition, this thesis also examines a closer integration of the multi-channel input with other robust speech recognition techniques. In addition to an experimental evaluation of key microphone array beamforming methods, several novel techniques are proposed. These include a near-field adaptive beamforming algorithm, an adaptive parameter compensation algorithm, and a multi-channel sub-band recognition system. Each of the proposed techniques is shown to offer significant performance improvements in speech recognition experiments in high noise conditions.
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Hua, Thanh Phong. "Adaptation mode controllers for adaptive microphone arrays." Rennes 1, 2006. http://www.theses.fr/2006REN1S136.

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Le traitement d’antenne réalisé par un réseau de microphones permet l’extraction d’un signal cible dans un environnement bruité. Dans ce travail, une calibration automatique est proposée pour supprimer la différence de gain entre les microphones tout en gardant la même puissance moyenne en sortie de l'antenne fixe. Deux nouveaux contrôleurs de mode d'adaptation (AMC pour Adaptation Mode Controller) sont proposés pour la mise à jour des coefficients des filtres suivant la situation détectée (présence de signal cible ou d’interférence). Ces AMC sont basés sur une estimation du rapport signal-à-interférence. Les résultats des évaluations dans un environnement réel montrent que les AMC proposés contribuent à une meilleure qualité du signal de sortie ainsi qu'à une augmentation du taux de reconnaissance vocale pouvant atteindre 31% en comparaison d’un AMC conventionnel. Ces systèmes sont intégrés au robot PaPeRo développé par NEC et destiné à vivre en interaction avec les humains.
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Books on the topic "Microphone arrays"

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Brandstein, Michael, and Darren Ward, eds. Microphone Arrays. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04619-7.

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Benesty, Jacob, Gongping Huang, Jingdong Chen, and Ningning Pan. Microphone Arrays. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-36974-2.

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1967-, Brandstein Michael, and Ward Darren 1970-, eds. Microphone arrays: Techniques and applications. Berlin: Springer, 2001.

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1967-, Brandstein Michael, and Ward Darren 1970-, eds. Microphone arrays: Signal processing techniques and applications. New York: Springer, 2001.

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Benesty, Jacob, Jingdong Chen, and Israel Cohen. Design of Circular Differential Microphone Arrays. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14842-7.

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Benesty, Jacob, and Jingdong Chen. Study and Design of Differential Microphone Arrays. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-33753-6.

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Rennie, Steven J. Variational probabilistic speech separation using microphone arrays. Ottawa: National Library of Canada, 2003.

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Brandstein, Michael. Microphone Arrays: Signal Processing Techniques and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001.

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Benesty, Jacob. Microphone array signal processing. Berlin: Springer, 2008.

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Phang, Khoman S. Adaptive microphone arrays using FIR and IIR filters. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1993.

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Book chapters on the topic "Microphone arrays"

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Benesty, Jacob, Gongping Huang, Jingdong Chen, and Ningning Pan. "Low-Rank Beamforming." In Microphone Arrays, 87–111. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36974-2_5.

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Benesty, Jacob, Gongping Huang, Jingdong Chen, and Ningning Pan. "Differential Beamforming." In Microphone Arrays, 139–67. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36974-2_7.

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Benesty, Jacob, Gongping Huang, Jingdong Chen, and Ningning Pan. "Binaural Beamforming." In Microphone Arrays, 183–204. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36974-2_9.

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Benesty, Jacob, Gongping Huang, Jingdong Chen, and Ningning Pan. "Introduction." In Microphone Arrays, 1–11. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36974-2_1.

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Benesty, Jacob, Gongping Huang, Jingdong Chen, and Ningning Pan. "Fundamentals of Microphone Array Processing." In Microphone Arrays, 25–56. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36974-2_3.

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Benesty, Jacob, Gongping Huang, Jingdong Chen, and Ningning Pan. "Limitations of Single Microphone Processing." In Microphone Arrays, 13–24. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36974-2_2.

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Benesty, Jacob, Gongping Huang, Jingdong Chen, and Ningning Pan. "Large Array Beamforming." In Microphone Arrays, 205–23. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36974-2_10.

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Benesty, Jacob, Gongping Huang, Jingdong Chen, and Ningning Pan. "Principal Component Analysis in Noise Reduction and Beamforming." In Microphone Arrays, 57–85. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36974-2_4.

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Benesty, Jacob, Gongping Huang, Jingdong Chen, and Ningning Pan. "Distortionless Beamforming." In Microphone Arrays, 113–38. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36974-2_6.

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Benesty, Jacob, Gongping Huang, Jingdong Chen, and Ningning Pan. "Adaptive Noise Cancellation." In Microphone Arrays, 169–81. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36974-2_8.

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Conference papers on the topic "Microphone arrays"

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Hoffman, Michael W., X. F. Lu, C. Pinkelman, and Z. Li. "Comparison of microphone-array configurations for three- and four-microphone arrays." In Optical Science, Engineering and Instrumentation '97, edited by Franklin T. Luk. SPIE, 1997. http://dx.doi.org/10.1117/12.279485.

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Martinson, E., and B. Fransen. "Dynamically reconfigurable microphone arrays." In 2011 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2011. http://dx.doi.org/10.1109/icra.2011.5979675.

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Gomes Lobato, Thiago Henrique, and Roland Sottek. "Super-Resolution of Sound Source Radiation Using Microphone Arrays and Artificial Intelligence." In Noise and Vibration Conference & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2023. http://dx.doi.org/10.4271/2023-01-1142.

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<div class="section abstract"><div class="htmlview paragraph">To empirically estimate the radiation of sound sources, a measurement with microphone arrays is required. These are used to solve an inverse problem that provides the radiation characteristics of the source. The resolution of this estimation is a function of the number of microphones used and their position due to spatial aliasing. To improve the radiation resolution for the same number of microphones compared to standard methods (Ridge and Lasso), a method based on normalizing flows is proposed that uses neural networks to learn empirical priors from the radiation data. The method then uses these learned priors to regularize the inverse source identification problem. The effects of different microphone arrays on the accuracy of the method is simulated in order to verify how much additional resolution can be obtained with the additional prior information.</div></div>
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Mosher, Marianne, Michael Watts, Srba Jovic, Stephen Jaeger, Marianne Mosher, Michael Watts, Srba Jovic, and Stephen Jaeger. "Calibration of microphone arrays for phased array processing." In 3rd AIAA/CEAS Aeroacoustics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1997. http://dx.doi.org/10.2514/6.1997-1678.

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Khalid, L., S. E. Nordholm, and H. H. Dam. "Design study on microphone arrays." In 2015 IEEE International Conference on Digital Signal Processing (DSP). IEEE, 2015. http://dx.doi.org/10.1109/icdsp.2015.7252064.

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Lovatello, Jacopo, Alberto Bernardini, and Augusto Sarti. "Steerable Circular Differential Microphone Arrays." In 2018 26th European Signal Processing Conference (EUSIPCO). IEEE, 2018. http://dx.doi.org/10.23919/eusipco.2018.8553083.

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Hillenbrand, J., S. Haberzettl, and G. M. Sessler. "Close-talking piezoelectret microphone-arrays." In 2011 IEEE 14th International Symposium on Electrets ISE 14. IEEE, 2011. http://dx.doi.org/10.1109/ise.2011.6084965.

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Taseska, Maja, and Emanuel A. P. Habets. "Spotforming using distributed microphone arrays." In 2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA). IEEE, 2013. http://dx.doi.org/10.1109/waspaa.2013.6701876.

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CARDOSO, CF, and PA NELSON. "DIRECTIVITY OF SPHERICAL MICROPHONE ARRAYS." In Spring Conference Acoustics 2004. Institute of Acoustics, 2023. http://dx.doi.org/10.25144/17968.

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McKinney, E. D., and V. E. DeBrunner. "Directionalizing adaptive multi-microphone arrays for hearing aids using cardioid microphones." In Proceedings of ICASSP '93. IEEE, 1993. http://dx.doi.org/10.1109/icassp.1993.319084.

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Reports on the topic "Microphone arrays"

1

Cohen, Z. Noise Reduction with Microphone Arrays for Speaker Identification. Office of Scientific and Technical Information (OSTI), December 2011. http://dx.doi.org/10.2172/1034487.

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Hall, Neal A., Kenneth Allen Peterson, Eric Paul Parker, Paul James Resnick, Murat Okandan, and Darwin Keith Serkland. Ultrasensitive directional microphone arrays for military operations in urban terrain. Office of Scientific and Technical Information (OSTI), November 2007. http://dx.doi.org/10.2172/934861.

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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.), May 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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Ricard, Gilbert L., Joel T. Kalb, Georges R. Garinther, Tomasz R. Letowski, and Timothy J. Mermagen. Assessment of a Binaural Microphone Array. Fort Belvoir, VA: Defense Technical Information Center, July 1997. http://dx.doi.org/10.21236/ada328025.

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Sawatari, Katsumi. The Visualization of the Sound by the Microphone Array System. Warrendale, PA: SAE International, May 2005. http://dx.doi.org/10.4271/2005-08-0169.

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Benyamin, Minas, and Geoffrey H. Goldman. Acoustic Detection and Tracking of a Class I UAS with a Small Tetrahedral Microphone Array. Fort Belvoir, VA: Defense Technical Information Center, September 2014. http://dx.doi.org/10.21236/ada610599.

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Hoffman, Jeffrey. Using Blind Source Separation and a Compact Microphone Array to Improve the Error Rate of Speech Recognition. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.5258.

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Hart, Carl R., and Gregory W. Lyons. A Measurement System for the Study of Nonlinear Propagation Through Arrays of Scatterers. Engineer Research and Development Center (U.S.), November 2020. http://dx.doi.org/10.21079/11681/38621.

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Various experimental challenges exist in measuring the spatial and temporal field of a nonlinear acoustic pulse propagating through an array of scatterers. Probe interference and undesirable high-frequency response plague typical approaches with acoustic microphones, which are also limited to resolving the pressure field at a single position. Measurements made with optical methods do not have such drawbacks, and schlieren measurements are particularly well suited to measuring both the spatial and temporal evolution of nonlinear pulse propagation in an array of scatterers. Herein, a measurement system is described based on a z-type schlieren setup, which is suitable for measuring axisymmetric phenomena and visualizing weak shock propagation. In order to reduce directivity and initiate nearly spherically-symmetric propagation, laser induced breakdown serves as the source for the nonlinear pulse. A key component of the schlieren system is a standard schliere, which allows quantitative schlieren measurements to be performed. Sizing of the standard schliere is aided by generating estimates of the expected light refraction from the nonlinear pulse, by way of the forward Abel transform. Finally, considerations for experimental sequencing, image capture, and a reconfigurable rod array designed to minimize spurious wave interactions are specified. 15.
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