Journal articles: '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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Poletti, Mark. "Three-dimensional sound recording using directional beams." Journal of the Acoustical Society of America 154, no. 4_supplement (October 1, 2023): A255. http://dx.doi.org/10.1121/10.0023453.

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The recording of three-dimensional spatial audio is typically carried out using microphone arrays that produce higher-order B-format responses, which are defined by spherical harmonics. Spherical harmonics provide a compact, orthonormal representation of the sound field, but can be intuitively challenging for general users because they do not have a direction, as opposed to typical microphones used in the audio industry. Furthermore, spherical microphone arrays typically use microphone angles based on Platonic solids which do not have intuitive directions such as front, rear, left, right, up, and down. This paper considers the use of sets of directional beams that have orthonormal properties in a similar manner to spherical harmonics. Sets of angles that have intuitive directions are used, and a method of approximating orthonormal beams is developed. The approach can also be applied to angles obtained from Platonic solids. Finally, a prototype microphone array that implements the directional recording format is described.

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Hoffman, Michael W. "Microphone Arrays." Journal of the Acoustical Society of America 112, no. 3 (September 2002): 793. http://dx.doi.org/10.1121/1.1500757.

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Liu, Yu. "Adaptive Array Reduction in Acoustic Beamforming (Virtual Presentation)." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 265, no. 1 (February 1, 2023): 6745–56. http://dx.doi.org/10.3397/in_2022_1021.

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Acoustic beamforming is a widely used source localisation technique where an array of microphones is placed in the acoustic far-field to gather unique contributions of acoustic pressure waves. The spatial and temporal relationship of these pressure contributions are sensitive to the microphone array design. To date, most acoustic beamformers are constructed using a spiral-based array configuration, yet in recent years, a new technique for developing array patterns has emerged that unlocks flexibility and convenient customisation, yielding improved acoustic source imaging to its predecessors. These arrays are developed using an iterative microphone removal process, known as an array reduction method. A cost-function is developed that combines the penalty of spatial aliasing images, known as sidelobes, and the resolution of the acoustic source, known as the main lobe. Microphones are iteratively removed from a larger initial array to arrive at an array with a desired number of microphones, frequency range and spatial constraints. The use of array reduction method arrays has expanded into array designs for o set source locations, irregular areas, and the most recent advancement, array pairing. This paper provides a brief summary of the development of the array reduction techniques and some example results of its application.

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Yu, Liang, Qixin Guo, Ning Chu, and Rui Wang. "Achieving 3D Beamforming by Non-Synchronous Microphone Array Measurements." Sensors 20, no. 24 (December 19, 2020): 7308. http://dx.doi.org/10.3390/s20247308.

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Beamforming technology is an essential method in acoustic imaging or reconstruction, which has been widely used in sound source localization and noise reduction. The beamforming algorithm can be described as all microphones in a plane simultaneously recording the source signal. The source position is then localized by maximizing the result of the beamformer. Evidence has shown that the accuracy of the sound source localization in a 2D plane can be improved by the non-synchronous measurements of moving the microphone array. In this paper, non-synchronous measurements are applied to 3D beamforming, in which the measurement array envelops the 3D sound source space to improve the resolution of the 3D space. The entire radiated object is covered better by a virtualized large or high-density microphone array, and the range of beamforming frequency is also expanded. The 3D imaging results are achieved in different ways: the conventional beamforming with a planar array, the non-synchronous measurements with orthogonal moving arrays, and the non-synchronous measurements with non-orthogonal moving arrays. The imaging results of the non-synchronous measurements are compared with the synchronous measurements and analyzed in detail. The number of microphones required for measurement is reduced compared with the synchronous measurement. The non-synchronous measurements with non-orthogonal moving arrays also have a good resolution in 3D source localization. The proposed approach is validated with a simulation and experiment.

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Tripia, Sirawit, Worakrit Thida, and Sorasak Danworaphong. "Designing of two-dimensional acoustic beamforming array using machine learning." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 268, no. 6 (November 30, 2023): 2594–604. http://dx.doi.org/10.3397/in_2023_0380.

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Acoustic beamforming arrays are used for locating sound sources and their performance is measured by their directivity pattern. Designing an acoustic beamforming array to meet specific performance requirements can be challenging and requires numerical optimization of various factors such as array width, microphone positions, and the number of microphones. This study employed a Deep Neural Network (DNN) approach to predict the arrangement of a two-dimensional acoustic beamforming array giving the desired beam pattern. The DNN was trained on 90,000 microphone array designs and beam patterns of 1-kHz sound. The prediction accuracy was evaluated based on the mean absolute errors (MAE) of beam patterns, frequency-averaged main lobe width (MLW), and maximum sidelobe level (MSL). The results for commonly designed arrays datasets such as Brüel & Kjær style array had a 26.54% error in beam patterns, 2.34 degree/m error in MLW, and 4.21 dB error in MSL. However, for predicted arrays generated by the random array designs, the results were more accurate, with deviations of 22.08% in beam patterns, 1.82 degree/m error in MLW, and 5.07 dB in MSL.

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Sakamoto, Shuichi, and Kosuke Katada. "Sound field recording using distributed spherical microphone arrays based on a virtual spherical model." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 268, no. 4 (November 30, 2023): 4925–30. http://dx.doi.org/10.3397/in_2023_0698.

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Binaural synthesis helps provide rich spatial information to users. Spherical microphone arrays and head-related transfer functions significantly aid in realizing the aforementioned approach. In a typical case, a spherical microphone array is set at the recording point, and listeners experience the sound binaurally as if they are at the recording point. However, in real situations, setting a microphone array at the recording point is not always feasible. In this study, we investigate binaural synthesis using an Auditory Display based on VIrtual SpherE (ADVISE) model with distributed spherical microphone arrays. In the proposed ADVISE-based method, the virtual sphere is set around the target point, and the sound pressure on the boundary of the virtual sphere is calculated based on recorded signals using spherical microphone arrays. The simulation results indicate that the proposed method can robustly synthesize sound fields even when the target point is far from the spherical microphone arrays.

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da Silva, Bruno, An Braeken, Kris Steenhaut, and Abdellah Touhafi. "Design Considerations When Accelerating an FPGA-Based Digital Microphone Array for Sound-Source Localization." Journal of Sensors 2017 (2017): 1–20. http://dx.doi.org/10.1155/2017/6782176.

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The use of microphone arrays for sound-source localization is a well-researched topic. The response of such sensor arrays is dependent on the quantity of microphones operating on the array. A higher number of microphones, however, increase the computational demand, making real-time response challenging. In this paper, we present a Filter-and-Sum based architecture and several acceleration techniques to provide accurate sound-source localization in real-time. Experiments demonstrate how an accurate sound-source localization is obtained in a couple of milliseconds, independently of the number of microphones. Finally, we also propose different strategies to further accelerate the sound-source localization while offering increased angular resolution.

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Ivanov, Artem. "Simple in-system control of microphone sensitivities in an array." Journal of Sensors and Sensor Systems 13, no. 1 (April 30, 2024): 81–88. http://dx.doi.org/10.5194/jsss-13-81-2024.

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Abstract. A method to perform measurements of microphone responses directly in the array of a sensor system is described. It can be applied in reverberant environments and does not require high instrumentation effort. Due to the use of internal hardware of the sensor system, the whole signal chain of microphone–preamplifier–analogue-to-digital converter is characterized. The method was successfully tested for calibration of two types of planar arrays constructed with micro-electromechanical system (MEMS) microphones. Presented experimental results illustrate achieved performance, and possible application scenarios are discussed.

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da Silva, Bruno, An Braeken, and Abdellah Touhafi. "FPGA-Based Architectures for Acoustic Beamforming with Microphone Arrays: Trends, Challenges and Research Opportunities." Computers 7, no. 3 (August 3, 2018): 41. http://dx.doi.org/10.3390/computers7030041.

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Over the past decades, many systems composed of arrays of microphones have been developed to satisfy the quality demanded by acoustic applications. Such microphone arrays are sound acquisition systems composed of multiple microphones used to sample the sound field with spatial diversity. The relatively recent adoption of Field-Programmable Gate Arrays (FPGAs) to manage the audio data samples and to perform the signal processing operations such as filtering or beamforming has lead to customizable architectures able to satisfy the most demanding computational, power or performance acoustic applications. The presented work provides an overview of the current FPGA-based architectures and how FPGAs are exploited for different acoustic applications. Current trends on the use of this technology, pending challenges and open research opportunities on the use of FPGAs for acoustic applications using microphone arrays are presented and discussed.

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Zhang, Yi, B. B. Shen, and S. J. Meng. "Research of HRTF Character of Head-Mounted Microphone Array." Applied Mechanics and Materials 743 (March 2015): 479–83. http://dx.doi.org/10.4028/www.scientific.net/amm.743.479.

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Head-mounted microphone array has practical applications in robot acoustic localization system and wearable anti-sniper positioning system. Usually, sound source localization methods are based on linear or nonlinear unblocked microphone arrays. But head-mounted microphone array is a kind of blocked arrays, with which it needs information of Head Related Transfer Function (HRTF) for precise localization. In this paper, we research the HRTF character of head-mounted microphone array for localization in high frequency band and low frequency band respectively, and design a localization algorithm for low frequency sound based on head-mounted microphone array to analysis the threshold between high and low frequency. Experimental results show that the Head-mounted Microphone Array causes diffraction effect for low frequency sound, and amplitude attenuation effect for high frequency sound, and when the low frequency band is limited into 1 KHz, the localization algorithm for low frequency realizes the best performance.

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Bjelic, Milos, and Miodrag Stanojevic. "Comparison of LMS adaptive beamforming techniques in microphone arrays." Serbian Journal of Electrical Engineering 12, no. 1 (2015): 1–16. http://dx.doi.org/10.2298/sjee1501001b.

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This paper discusses principles of microphone array beamforming, specifically the use of LMS algorithm with training sequence. The problem of wideband nature of acoustical signals and its impact on the techniques of beamforming are discussed. Detailed explanation of classic narrowband and wideband LMS beamformers is presented, as well as the modification of narrowband algorithm with pre-steering. Experimental testing and comparison of algorithm performances was conducted and measurement results are presented. The used microphone array is part of Br?el & Kj?r acoustical camera, and is comprised of 18 omnidirectional non-uniformly spaced microphones.

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ma, fei, Sipei Zhao, and Thushara Abhayapala. "Physics-informed neural network assisted spherical microphone array signal processing." Journal of the Acoustical Society of America 154, no. 4_supplement (October 1, 2023): A182. http://dx.doi.org/10.1121/10.0023200.

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Thanks to their rotational symmetry that facilitates three-dimensional signal processing, spherical microphone arrays are the common array apertures used for spatial audio and acoustic applications. However, practical implementations of spherical microphone arrays suffer from two issues. First, at high frequency range, a large number of sensors are needed to accurately capture a sound field. Second, the accompanying signal processing algorithm, i.e., the spherical harmonic decomposition method, requires a variable radius array or a rigid surface array to circumvent the spherical Bessel function nulls. Such arrays are hard to design and introduce a scattering field. To address these issues, this paper proposes to assist a spherical microphone array with a physics-informed neural network (PINN) for three-dimensional signal processing. The PINN models the sound field around the array based on the sensor measurements and the acoustic wave equation, augmenting the sound field information captured by the array through prediction. This makes it possible to analyze a high frequency sound field with a reduced number of sensors and avoid the spherical Bessel function nulls with a simple single radius open-sphere microphone array.

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Yu, Jing Jing, and Fa Shan Yu. "Evolutionary Algorithm for Microphone Array Optimization." Applied Mechanics and Materials 143-144 (December 2011): 287–92. http://dx.doi.org/10.4028/www.scientific.net/amm.143-144.287.

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This paper presented a genetic algorithm (GA) to optimize element placements of microphone array with the purpose of maximizing beamforming SNR for given possible distribution of sound sources. A function based on relationship between statistical geometry descriptors and array performance matrices was applied as the objective function of GA. Optimization experiments of 1D linear array and 2D planar array were performed to demonstrate that this algorithm can effectively sort out superior arrays with significant SNR improvements over randomly generated arrays and regular arrays. High successful rate, rapid convergence speed, and fast processing time observed in all the experiments demonstrate the feasibility of this algorithm as a practical tool for microphone array design.

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Gnamele, N’tcho Assoukpou Jean, Bi Tra Jean Claude Youan, and Adjoua Moise Landry Famien. "Improvement of chainsaw sounds identification in the forest environment using maximum ratio combining and classification algorithme." EUREKA: Physics and Engineering, no. 3 (May 27, 2024): 3–16. http://dx.doi.org/10.21303/2461-4262.2024.003107.

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To better combat the devastation of the protected forests in Côte d’Ivoire, a study was conducted to create a technique for detecting the acoustic signals produced by chainsaws deployed to fell trees in these areas. To improve the recognition rate of chainsaw sounds in a forest environment and increase the detection range of the recognition system, we are implementing the maximum ratio combining (MRC) technique on a microphone array. Therefore, the employment of an identification system is compared using one (01) microphone against the outcomes obtained by adopting system with three (03), six (06), and twelve (12) microphones. The use of MRC is then contrasted with an alternative recombining approach, referred to as simple summation (SS). The SS is characterized by the mere addition of signals acquired by the network in the frequency domain. The MRC was employed on various microphone arrangements, accounting for varying degrees of attenuation experienced by chainsaw sounds. The K-Nearest Neighbors, in combination with Mel Frequency Cepstral Coefficients (MFCC), was employed to detect chainsaw sounds within the 16 kHz central frequency octave band. MRC applied to microphone arrays provided superior outcomes than simple summation. The enhancement in terms of classification rate ranged from [18; 51], favouring MRC. Moreover, it extended the chainsaw detection range from 520 m (using one microphone) to 1210 m (using a 12-microphone array). Taking into account the criteria for selecting an optimum microphone array, including classification rate, number of microphone nodes, information processing time and detection range, the six-microphone array was chosen as the best configuration. This configuration boasts a theoretical detection range of 1040 meters

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Kondo, Kazunobu, Yusuke Mizuno, Takanori Nishino, and Kazuya Takeda. "Practically Efficient Blind Speech Separation Using Frequency Band Selection Based on Magnitude Squared Coherence and a Small Dodecahedral Microphone Array." Journal of Electrical and Computer Engineering 2012 (2012): 1–11. http://dx.doi.org/10.1155/2012/324398.

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Small agglomerative microphone array systems have been proposed for use with speech communication and recognition systems. Blind source separation methods based on frequency domain independent component analysis have shown significant separation performance, and the microphone arrays are small enough to make them portable. However, the level of computational complexity involved is very high because the conventional signal collection and processing method uses 60 microphones. In this paper, we propose a band selection method based on magnitude squared coherence. Frequency bands are selected based on the spatial and geometric characteristics of the microphone array device which is strongly related to the dodecahedral shape, and the selected bands are nonuniformly spaced. The estimated reduction in the computational complexity is 90% with a 68% reduction in the number of frequency bands. Separation performance achieved during our experimental evaluation was 7.45 (dB) (signal-to-noise ratio) and 2.30 (dB) (cepstral distortion). These results show improvement in performance compared to the use of uniformly spaced frequency band.

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Liaquat, Muhammad Usman, Hafiz Suliman Munawar, Amna Rahman, Zakria Qadir, Abbas Z. Kouzani, and M. A. Parvez Mahmud. "Sound Localization for Ad-Hoc Microphone Arrays." Energies 14, no. 12 (June 10, 2021): 3446. http://dx.doi.org/10.3390/en14123446.

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Sound localization is a field of signal processing that deals with identifying the origin of a detected sound signal. This involves determining the direction and distance of the source of the sound. Some useful applications of this phenomenon exists in speech enhancement, communication, radars and in the medical field as well. The experimental arrangement requires the use of microphone arrays which record the sound signal. Some methods involve using ad-hoc arrays of microphones because of their demonstrated advantages over other arrays. In this research project, the existing sound localization methods have been explored to analyze the advantages and disadvantages of each method. A novel sound localization routine has been formulated which uses both the direction of arrival (DOA) of the sound signal along with the location estimation in three-dimensional space to precisely locate a sound source. The experimental arrangement consists of four microphones and a single sound source. Previously, sound source has been localized using six or more microphones. The precision of sound localization has been demonstrated to increase with the use of more microphones. In this research, however, we minimized the use of microphones to reduce the complexity of the algorithm and the computation time as well. The method results in novelty in the field of sound source localization by using less resources and providing results that are at par with the more complex methods requiring more microphones and additional tools to locate the sound source. The average accuracy of the system is found to be 96.77% with an error factor of 3.8%.

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Takeuchi, Ren, Itsuki Ikemi, Kazunori Harada, Akiko Sugahara, and Yasuhiro Hiraguri. "A study on the influence of reflective surfaces on sound source localization using distributed acoustic measurement equipment." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 268, no. 1 (November 30, 2023): 7032–37. http://dx.doi.org/10.3397/in_2023_1052.

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This research aims to develop a system that will detect sound source localization in a broad area using cross-correlation functions for signals from distributed microphone arrays, which is difficult with conventional methods that use microphone arrays. For the localization of sound sources, four microphones were distributed in an anechoic room. Based on the result, the system was able to estimate the sound source position within a plus or minus 20 mm of accuracy. To verify the accuracy of the system, a reflective surface was set up in an anechoic room to confirm the effect of reflected and diffracted sound. No significant increase in error was observed when the reflective surface was behind the microphone as viewed from the sound source. However, the estimation error increased when diffracted sound was present.

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Grubeša, Sanja, Jasna Stamać, Mia Suhanek, and Antonio Petošić. "Use of Genetic Algorithms for Design an FPGA-Integrated Acoustic Camera." Sensors 22, no. 8 (April 8, 2022): 2851. http://dx.doi.org/10.3390/s22082851.

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The goal of this paper is to design a broadband acoustic camera using micro-electromechanical system (MEMS) microphones. The paper describes how an optimization of the microphone array has been carried out. Furthermore, the final goal of the described optimization is that the gain in the desired direction and the attenuation of side lobes is maximized at a frequency up to 4 kHz. Throughout the research, various shapes of microphone arrays and their directivity patterns have been considered and analyzed using newly developed algorithms implemented in Matlab. A hemisphere algorithm, genetic algorithm, and genetic square algorithm were used to find the optimal position and number of microphones placed on an acoustic camera. The proposed acoustic camera design uses a large number of microphones for high directional selectivity, while a field programmable gate array system on a chip (FPGA SoC) is selected as the processing element of the system. According to the obtained results, three different acoustic camera prototypes were developed. This paper presents simulations of their characteristics, compares the obtained measurements, and discusses the positive and negative sides of each acoustic camera prototype.

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da Silva, Bruno, An Braeken, Federico Domínguez, and Abdellah Touhafi. "Exploiting Partial Reconfiguration through PCIe for a Microphone Array Network Emulator." International Journal of Reconfigurable Computing 2018 (2018): 1–16. http://dx.doi.org/10.1155/2018/3214679.

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The current Microelectromechanical Systems (MEMS) technology enables the deployment of relatively low-cost wireless sensor networks composed of MEMS microphone arrays for accurate sound source localization. However, the evaluation and the selection of the most accurate and power-efficient network’s topology are not trivial when considering dynamic MEMS microphone arrays. Although software simulators are usually considered, they consist of high-computational intensive tasks, which require hours to days to be completed. In this paper, we present an FPGA-based platform to emulate a network of microphone arrays. Our platform provides a controlled simulated acoustic environment, able to evaluate the impact of different network configurations such as the number of microphones per array, the network’s topology, or the used detection method. Data fusion techniques, combining the data collected by each node, are used in this platform. The platform is designed to exploit the FPGA’s partial reconfiguration feature to increase the flexibility of the network emulator as well as to increase performance thanks to the use of the PCI-express high-bandwidth interface. On the one hand, the network emulator presents a higher flexibility by partially reconfiguring the nodes’ architecture in runtime. On the other hand, a set of strategies and heuristics to properly use partial reconfiguration allows the acceleration of the emulation by exploiting the execution parallelism. Several experiments are presented to demonstrate some of the capabilities of our platform and the benefits of using partial reconfiguration.

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Elko, Gary W., and Jens Meyer. "Small aperture microphone arrays." Journal of the Acoustical Society of America 138, no. 3 (September 2015): 1736. http://dx.doi.org/10.1121/1.4933471.

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Flanagan, J. L. "Three‐dimensional microphone arrays." Journal of the Acoustical Society of America 82, S1 (November 1987): S39. http://dx.doi.org/10.1121/1.2024789.

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Liaquat, Muhammad Usman, Hafiz Suliman Munawar, Amna Rahman, Zakria Qadir, Abbas Z. Kouzani, and M. A. Parvez Mahmud. "Localization of Sound Sources: A Systematic Review." Energies 14, no. 13 (June 29, 2021): 3910. http://dx.doi.org/10.3390/en14133910.

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Sound localization is a vast field of research and advancement which is used in many useful applications to facilitate communication, radars, medical aid, and speech enhancement to but name a few. Many different methods are presented in recent times in this field to gain benefits. Various types of microphone arrays serve the purpose of sensing the incoming sound. This paper presents an overview of the importance of using sound localization in different applications along with the use and limitations of ad-hoc microphones over other microphones. In order to overcome these limitations certain approaches are also presented. Detailed explanation of some of the existing methods that are used for sound localization using microphone arrays in the recent literature is given. Existing methods are studied in a comparative fashion along with the factors that influence the choice of one method over the others. This review is done in order to form a basis for choosing the best fit method for our use.

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Wang, Dong-xia, Mao-song Jiang, Fang-lin Niu, Yu-dong Cao, and Cheng-xu Zhou. "Speech Enhancement Control Design Algorithm for Dual-Microphone Systems Using β-NMF in a Complex Environment." Complexity 2018 (September 9, 2018): 1–13. http://dx.doi.org/10.1155/2018/6153451.

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Single-microphone speech enhancement algorithms by using nonnegative matrix factorization can only utilize the temporal and spectral diversity of the received signal, making the performance of the noise suppression degrade rapidly in a complex environment. Microphone arrays have spatial selection and high signal gain, so it applies to the adverse noise conditions. In this paper, we present a new algorithm for speech enhancement based on two microphones with nonnegative matrix factorization. The interchannel characteristic of each nonnegative matrix factorization basis can be modeled by the adopted method, such as the amplitude ratios and the phase differences between channels. The results of the experiment confirm that the proposed algorithm is superior to other dual-microphone speech enhancement algorithms.

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Movahed, Ali, Thomas Waschkies, and Ute Rabe. "Air Ultrasonic Signal Localization with a Beamforming Microphone Array." Advances in Acoustics and Vibration 2019 (February 11, 2019): 1–12. http://dx.doi.org/10.1155/2019/7691645.

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Nondestructive testing methods are used to inspect and test materials and components for discontinuities or differences in mechanical characteristics. Phased array signal processing techniques have been widely used in different applications, but less research has been conducted on contactless nondestructive testing with passive arrays. This paper presents an application of beamforming techniques analysis using a passive synthetic microphone array to calculate the origin and intensity of sound waves in the ultrasonic frequency range. Acoustic cameras operating in the audible frequency range are well known. In order to conduct measurements in higher frequencies, the arrangement of microphones in an array has to be taken into consideration. This arrangement has a strong influence on the array properties, such as its beam pattern, its dynamics, and its susceptibility to spatial aliasing. Based on simulations, optimized configurations with 16, 32, and 48 microphones and 20 cm diameter were implemented in real experiments to investigate the array resolution and localize ultrasonic sources at 75 kHz signal frequency. The results show that development of an ultrasonic camera to localize ultrasonic sound sources is beneficial.

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Zhang, Xin, Enliang Song, JingChang Huang, Huawei Liu, YuePeng Wang, Baoqing Li, and Xiaobing Yuan. "Acoustic Source Localization via Subspace Based Method Using Small Aperture MEMS Arrays." Journal of Sensors 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/675726.

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Small aperture microphone arrays provide many advantages for portable devices and hearing aid equipment. In this paper, a subspace based localization method is proposed for acoustic source using small aperture arrays. The effects of array aperture on localization are analyzed by using array response (array manifold). Besides array aperture, the frequency of acoustic source and the variance of signal power are simulated to demonstrate how to optimize localization performance, which is carried out by introducing frequency error with the proposed method. The proposed method for 5 mm array aperture is validated by simulations and experiments with MEMS microphone arrays. Different types of acoustic sources can be localized with the highest precision of 6 degrees even in the presence of wind noise and other noises. Furthermore, the proposed method reduces the computational complexity compared with other methods.

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Shi, Hetian, Yi He, Qing Wang, Jianwei Zhuge, Qi Li, and Xin Liu. "Laser-Based Command Injection Attacks on Voice-Controlled Microphone Arrays." IACR Transactions on Cryptographic Hardware and Embedded Systems 2024, no. 2 (March 12, 2024): 654–76. http://dx.doi.org/10.46586/tches.v2024.i2.654-676.

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Voice-controlled (VC) systems, such as mobile phones and smart speakers, enable users to operate smart devices through voice commands. Previous works (e.g., LightCommands) show that attackers can trigger VC systems to respond to various audio commands by injecting light signals. However, LightCommands only discusses attacks on devices with a single microphone, while new devices typically use microphone arrays with sensor fusion technology for better capturing sound from different distances. By replicating LightCommands’s experiments on the new devices, we find that simply extending the light scope (just as they do) to overlap multiple microphone apertures is inadequate to wake up the device with sensor fusion. Adapting LightCommands’s approach to microphone arrays is challenging due to their requirement for multiple sound amplifiers, and each amplifier requires an independent power driver with unique settings. The number of additional devices increases with the microphone aperture count, significantly increasing the complexity of implementing and deploying the attack equipment. With a growing number of devices adopting sensor fusion to distinguish the sound location, it is essential to propose new approaches to adapting the light injection attacks to these new devices. To address these problems, we propose a lightweight microphone array laser injection solution called LCMA (Laser Commands for Microphone Array), which can use a single laser controller to manipulate multiple laser points and simultaneously target all the apertures of a microphone array and input light waves at different frequencies. Our key design is to propose a new PWM (Pulse Width Modulation) based control signal algorithm that can be implemented on a single MCU and directly control multiple lasers via different PWM output channels. Moreover, LCMA can be remotely configured via BLE (Bluetooth Low Energy). These features allow our solution to be deployed on a drone to covertly attack the targets hidden inside the building. Using LCMA, we successfully attack 29 devices. The experiment results show that LCMA is robust on the newest devices such as the iPhone 15, and the control panel of the Tesla Model Y.

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Ciric, Dejan, Ana Djordjevic, and Marko Licanin. "Analysis of effects of spherical microphone array physical parameters using simulations." Facta universitatis - series: Electronics and Energetics 26, no. 2 (2013): 107–19. http://dx.doi.org/10.2298/fuee1302107c.

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Spherical microphone arrays are used for spatial sound field analysis. Although there are commercially available products, they are not the most suitable for research due to their price and working limits of the embedded software. In those cases it is more convenient to build an own prototype in a lab. In this paper, the analysis of the effects of the physical parameters of a spherical microphone array is presented. The observed parameters are radius of the sphere, distance from the sound source and distribution of the microphone elements points over the sphere. The obtained results provide useful inputs for building a spherical microphone array for the desired applications.

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Sarkar, Kanad, Manan Mittal, Ryan M. Corey, and Andrew C. Singer. "Manifold learning for dynamic array geometries." Journal of the Acoustical Society of America 152, no. 4 (October 2022): A143. http://dx.doi.org/10.1121/10.0015835.

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Large-scale distributed arrays can obtain high spatial resolution, but they typically rely on a rigid array structure. If we want to form distributed arrays from mobile and wearable devices, our models need to account for motion. The motion of multiple microphones worn by humans can be difficult to track, but through manifold techniques we can learn the movement through its acoustic response. We show that the mapping between the array geometry and its acoustic response is locally linear and can be exploited in a semi-supervised manner for a given acoustic environment. We will also investigate generative modelling of microphone positions based on their acoustic response to both synthetic and recorded data. Prior work has shown a similar locally linear mapping between source locations and their spatial cues, and we will attempt to combine these findings with our own to develop a localization model suitable for dynamic array geometries.

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Elko, Gary W., James E. West, and Steve Thompson. "Differential and gradient microphone arrays." Journal of the Acoustical Society of America 114, no. 4 (October 2003): 2426. http://dx.doi.org/10.1121/1.4778848.

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Lau, B. K., Y. H. Leung, K. L. Teo, and V. Steeram. "Minimax filters for microphone arrays." IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 46, no. 12 (1999): 1522–24. http://dx.doi.org/10.1109/82.809540.

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Lockwood, Michael E., Douglas L. Jones, Quang Su, and Ronald N. Miles. "Beamforming with collocated microphone arrays." Journal of the Acoustical Society of America 114, no. 4 (October 2003): 2451. http://dx.doi.org/10.1121/1.4779498.

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Aarabi, P. "Self-localizing dynamic microphone arrays." IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) 32, no. 4 (November 2002): 474–84. http://dx.doi.org/10.1109/tsmcb.2002.804369.

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Meyer, Jens, and Gary W. Elko. "Eigenbeam beamforming for microphone arrays." Journal of the Acoustical Society of America 120, no. 5 (November 2006): 3177. http://dx.doi.org/10.1121/1.4787960.

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Qiguang Lin, Ea-Ee Jan, and J. Flanagan. "Microphone arrays and speaker identification." IEEE Transactions on Speech and Audio Processing 2, no. 4 (1994): 622–29. http://dx.doi.org/10.1109/89.326620.

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Biswas, Shantonu, Johannes Reiprich, Thaden Cohrs, David T. Arboleda, Andreas Schoeberl, Mahsa Mozafari, Leslie Schlag, Thomas Stauden, Joerg Pezoldt, and Heiko O. Jacobs. "3D Metamorphic Stretchable Microphone Arrays." Advanced Materials Technologies 2, no. 10 (August 1, 2017): 1700131. http://dx.doi.org/10.1002/admt.201700131.

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Wills, Angus, Manuj Awasthi, Charitha de Silva, Danielle Moreau, and Con Doolan. "Design and characterisation of a 3-D microphone array for windtunnel measurements." Journal of the Acoustical Society of America 154, no. 4_supplement (October 1, 2023): A103. http://dx.doi.org/10.1121/10.0022935.

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A three-dimensional (3-D) array of GRAS 40PH-10 CCP Free-field Array Microphones has been designed for use in the UNSW anechoic wind tunnel (UAT) for aeroacoustic measurements. The array consists of 192 microphones split into three identical planar arrays of 64 microphones which are placed on both sides and above the potential core of the open-jet that issues into the wind tunnel test section. The planar arrays feature an Underbrink spiral comprised of eight arms of eight microphones each. The spiral configuration was selected to maximize signal-to-noise ratio (SNR) and minimize the beamwidth given the geometrical restrictions of the UAT. A white noise speaker was placed at a range of locations within the testing domain to characterize the source localization abilities of the array as a function of position and frequency. Furthermore, a pair of independent white noise speakers were placed at various separation distances to determine the array’s capability to identify multiple sources within the domain. A 3-D implementation of conventional cross-spectral beamforming and Clean-SC deconvolution algorithms was used, and the performance of each was compared. It was determined that Clean-SC was the preferred method for 3-D beamforming in terms of source localization accuracy, SNR, and beamwidth, despite the higher computational cost.

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Sun, Huiyuan, Thushara D. Abhayapala, and Prasanga N. Samarasinghe. "Time Domain Spherical Harmonic Processing with Open Spherical Microphones Recording." Applied Sciences 11, no. 3 (January 25, 2021): 1074. http://dx.doi.org/10.3390/app11031074.

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Spherical harmonic analysis has been a widely used approach for spatial audio processing in recent years. Among all applications that benefit from spatial processing, spatial Active Noise Control (ANC) remains unique with its requirement for open spherical microphone arrays to record the residual sound field throughout the continuous region. Ideally, a low delay spherical harmonic recording algorithm for open spherical microphone arrays is desired for real-time spatial ANC systems. Currently, frequency domain algorithms for spherical harmonic decomposition of microphone array recordings are applied in a spatial ANC system. However, a Short Time Fourier Transform is required, which introduces undesirable system delay for ANC systems. In this paper, we develop a time domain spherical harmonic decomposition algorithm for the application of spatial audio recording mainly with benefit to ANC with an open spherical microphone array. Microphone signals are processed by a series of pre-designed finite impulse response (FIR) filters to obtain a set of time domain spherical harmonic coefficients. The time domain coefficients contain the continuous spatial information of the residual sound field. We corroborate the time domain algorithm with a numerical simulation of a fourth order system, and show the proposed method to have lower delay than existing approaches.

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Le, Nguyen, Jenny Y. Au, Kavitha Chandra, and Charles Thompson. "Synthesis of nonuniformly spaced arrays." Journal of the Acoustical Society of America 153, no. 3_supplement (March 1, 2023): A362. http://dx.doi.org/10.1121/10.0019167.

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This work presents an analysis of beam formation from nonuniformly spaced planar microphone arrays. The effect of transducers' random and deterministic placement on the array's response characteristics is considered. Arrays that exhibit maximal sidelobe reduction are of particular interest. A solution for the transducer density as a function of the position is given.

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Sanguineti, Valentina, Pietro Morerio, Alessio Del Bue, and Vittorio Murino. "Audio-Visual Localization by Synthetic Acoustic Image Generation." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 3 (May 18, 2021): 2523–31. http://dx.doi.org/10.1609/aaai.v35i3.16354.

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Acoustic images constitute an emergent data modality for multimodal scene understanding. Such images have the peculiarity to distinguish the spectral signature of sounds coming from different directions in space, thus providing richer information than the one derived from mono and binaural microphones. However, acoustic images are typically generated by cumbersome microphone arrays, which are not as widespread as ordinary microphones mounted on optical cameras. To exploit this empowered modality while using standard microphones and cameras we propose to leverage the generation of synthetic acoustic images from common audio-video data for the task of audio-visual localization. The generation of synthetic acoustic images is obtained by a novel deep architecture, based on Variational Autoencoder and U-Net models, which is trained to reconstruct the ground truth spatialized audio data collected by a microphone array, from the associated video and its corresponding monaural audio signal. Namely, the model learns how to mimic what an array of microphones can produce in the same conditions. We assess the quality of the generated synthetic acoustic images on the task of unsupervised sound source localization in a qualitative and quantitative manner, while also considering standard generation metrics. Our model is evaluated by considering both multimodal datasets containing acoustic images, used for the training, and unseen datasets containing just monaural audio signals and RGB frames, showing to reach more accurate localization results as compared to the state of the art.

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Wang, Ningning, Yonghe Wei, and Zonglin Li. "Research on multi-sound source localization performance based on leaf-shaped microphone array." Journal of Physics: Conference Series 2479, no. 1 (April 1, 2023): 012026. http://dx.doi.org/10.1088/1742-6596/2479/1/012026.

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Abstract In the research of multi-sound source localization, the geometric rules for the spatial arrangement of microphone arrays play a decisive role. When faced with multiple sound sources with close positions, traditional typical arrays are difficult to accurately locate the desired signals. Therefore, this paper proposes a leaf-shaped microphone array based on the theory of bionic sunflower spiral arrangement. When the incident signals are multiple sound sources with close positions, combined with the delay-sum beamforming algorithm, the performance of the leaf-shaped array is analyzed from the perspective of positioning accuracy and resolution. Compared with the uniform circular array and Arcondoulis spiral array, the results show that the leaf-shaped array has better resolution and anti-interference ability in the case of multiple sound sources with close positions.

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Journal articles on the topic 'Microphone arrays'

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