Microphone Array System Research Articles

AES67 based microphone array for sound source localization

Within the research project EAV-Infra, a novel microphone array system was developed. The system stands out for its utilization of Ethernet-based signal, control data and power transmission, ensuring a high degree of flexibility in operation. The key feature is its ability to facilitate real-time multichannel audio streaming via AES67, allowing for scalable and distributed recording and computing. With a total of 64 digital miniaturized microphones integrated into its printed circuit board-based design, the system allows for analysis of audio data for beamforming and other sound localization mechanisms. Adherence to audio and networking standards ensures synchronized transmission of audio data over packet-based networks. The system's emphasis on scalability, flexibility, and affordability makes it well-suited for a wide range of applications in fields like acoustic metrology and the entertainment industry, providing a comprehensive solution for high-quality audio processing needs across diverse domains.

Designing a smart classroom with advanced Audiovisual equipment and soft collaboration capabilities for Higher Education

This is a technology-enabled classroom design which reflects a thoughtful integration of cutting-edge audiovisual solutions to enhance the learning environment. The inclusion of automated audio-visual solutions indicates a commitment to creating a seamless and efficient learning experience through technology. The incorporation of a voice lift application ensures clear and audible communication for the instructor, addressing potential challenges in large classroom settings. The use of Dante-based communication over Ethernet signifies a high-quality and reliable audio distribution system, enabling efficient communication within the classroom. The inclusion of features catering to individuals with disabilities demonstrates a commitment to creating an inclusive and accessible learning environment. The beamforming microphone array system with multiple elements is a sophisticated technology that allows for effective tracking of the active participant. This ensures that the audio focus adapts to the speaker's location. The automatic and steerable coverage type enhances the adaptability of the microphone array system, automatically focusing on the speaker. This feature contributes to an immersive and dynamic learning experience. The support for Power over Ethernet (PoE) simplifies the installation and management of AV devices in the classroom. It reduces the need for additional power outlets and cables, streamlining the overall setup. Overall, this design prioritizes advanced audiovisual technologies to create a unique, state-of-the-art, and inclusive technology-enabled classroom. The focus on clear communication, adaptability, and ease of use demonstrates a commitment to providing an optimal learning environment for both faculty and students

Verification and application of the aircraft noise simulation framework J-FRAIN

We newly developed a framework for aircraft noise simulation, J-FRAIN, that can precisely predict the noise from aircraft at ground observation points during the landing approach phase. J-FRAIN enables the incorporation of component-wise regression sound source models created from field measurement data using a microphone array system and the precise prediction of the time history of noise from each aircraft component. To verify the noise prediction accuracy of J-FRAIN, noise prediction of the landing approach phase around an airport was performed. The component-wise regression sound source models created from the data measured at the location just before touch-down was used since its regression model can estimate the sound power levels at flight parameters not only actually measured but also not measured. The predicted result and noise measured by aircraft noise monitoring systems were verified to be in good agreement. As examples of the application using J-FRAIN, two case studies were also discussed; the determination of the contribution of each noise source at observation points and the evaluation of the influence of flight parameter differences on noise levels at observation points.

A novel audio-visual based beamformer using a 360° camera and planar microphone array system

Beamforming systems that rely only on microphone arrays may suffer from poor performance in complex acoustic environments with multiple sources and room reverberation. To overcome this limitation, we propose a novel method that combines a planar microphone array and a 360° camera to steer the beamformer. The camera provides visual information about the location and orientation of sound sources, which can be used to adjust the beamformer parameters. We will present results that compare the signal-to-noise ratio (SNR) of the proposed method with a conventional beamforming microphone-based method in a simulated room with different source positions, orientations, and noise levels to investigate the benefit of visual information for beamforming in different environments. The proposed method has the potential to improve the performance of beamforming systems in applications such as speech enhancement, speech recognition, and speaker localization.

Rotor Noise-Aware Noise Covariance Matrix Estimation for Unmanned Aerial Vehicle Audition

A noise covariance matrix (NCM) estimation method for unmanned aerial vehicle (UAV) audition is proposed with rotor noise reduction as its primary focus. The proposed NCM estimation method could be incorporated into audio processing algorithms using UAV-mounted microphone array systems. The NCM is formed through accurate estimation of the microphone array input signal's amplitude and phase by using a multi-sensory rotor noise power spectral density (PSD) estimator and a filter formed by exploiting the acoustical relationship between the microphone array and the rotor noise sources, respectively. The estimated NCM aims to be readily incorporable into several source enhancement algorithms to reduce the effects of rotor noise and improve the resultant audio quality. Experiment evaluation using real in-flight UAV rotor noise recordings shows that the estimated NCM significantly improves rotor noise reduction (of up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sim 28$</tex-math></inline-formula> dB) and the quality of the target sound.

TESTING A NOVEL HYBRID SPIRAL MICROPHONE ARRAY DESIGNED FOR PERFORMANCE AND PORTA

In this investigation a novel hybrid spiral microphone array system is designed and constructed to maximize the overall performance of the array under the constraint that the array must be portable and capable of being transported in a small hatchback vehicle. Several microphone array designs are considered before settling on a modified Fermat spiral with microphones located exclusively on the axes of the array, enabling the array to be quickly disassembled into a small number of sections, transported to a remote location, and then re-assembled. The performance of the new microphone array is tested against an existing microphone array that was also designed for portability but with a more conventional logarithmic spiral design. The resolution of the new hybrid spiral array is found to greatly exceed the resolution of the conventional portable microphone array.

Sound Localization Based on Acoustic Source Using Multiple Microphone Array in an Indoor Environment

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.

Deep Learning-Enabled High-Resolution and Fast Sound Source Localization in Spherical Microphone Array System

While sound source localization (SSL) using a spherical microphone array system can be applied to obtain visual beam patterns of source distribution maps in a range of omnidirectional acoustic applications, the present challenges of the spherical measurement system on the valid frequency ranges and the spatial distortion as well as the grid-related limitations of data-driven SSL approaches raise the need to develop an appropriate method. Imbued by these challenges, this study proposes a deep learning approach to achieve the high-resolution performance of localizing multiple sound sources tailored for omnidirectional acoustic applications. First, we present a spherical target map representation that can panoramically pinpoint the position and strength information of multiple sound sources without any grid-related constraints. Then, a dual-branched spherical convolutional autoencoder is proposed to obtain high-resolution localization results from the conventional spherical beamforming maps while incorporating frequency-variant and distortion-invariant strategies to address the inherent challenges. We quantitatively and qualitatively assess our proposed method’s localization capability for multiple sound sources and validate that the proposed method can achieve far more precise and computationally-efficient results than the existing approaches. By extension, we newly present the experimental setup that can create omnidirectional acoustic scenarios for the multiple sound source localization. By evaluating our proposed method in this experimental setup, we demonstrate the effectiveness and applicability of the proposed method with the experimental data. Our study delivers the proposed approach’s potential of being utilized in various sound source localization applications.

Bio-acoustic tracking and localization using heterogeneous, scalable microphone arrays

Microphone arrays are an essential tool in the field of bioacoustics as they provide a non-intrusive way to study animal vocalizations and monitor their movement and behavior. Microphone arrays can be used for passive localization and tracking of sound sources while analyzing beamforming or spatial filtering of the emitted sound. Studying free roaming animals usually requires setting up equipment over large areas and attaching a tracking device to the animal which may alter their behavior. However, monitoring vocalizing animals through arrays of microphones, spatially distributed over their habitat has the advantage that unrestricted/unmanipulated animals can be observed. Important insights have been achieved through the use of microphone arrays, such as the convergent acoustic field of view in echolocating bats or context-dependent functions of avian duets. Here we show the development and application of large flexible microphone arrays that can be used to localize and track any vocalizing animal and study their bio-acoustic behavior. In a first experiment with hunting pallid bats the acoustic data acquired from a dense array with 64 microphones revealed details of the bats’ echolocation beam in previously unseen resolution. We also demonstrate the flexibility of the proposed microphone array system in a second experiment, where we used a different array architecture allowing to simultaneously localize several species of vocalizing songbirds in a radius of 75 m. Our technology makes it possible to do longer measurement campaigns over larger areas studying changing habitats and providing new insights for habitat conservation. The flexible nature of the technology also makes it possible to create dense microphone arrays that can enhance our understanding in various fields of bioacoustics and can help to tackle the analytics of complex behaviors of vocalizing animals.

Prototype Development of Cross-Shaped Microphone Array System for Drone Localization Based on Delay-and-Sum Beamforming in GNSS-Denied Areas

Drones equipped with a global navigation satellite system (GNSS) receiver for absolute localization provide high-precision autonomous flight and hovering. However, the GNSS signal reception sensitivity is considerably lower in areas such as those between high-rise buildings, under bridges, and in tunnels. This paper presents a drone localization method based on acoustic information using a microphone array in GNSS-denied areas. Our originally developed microphone array system comprised 32 microphones installed in a cross-shaped configuration. Using drones of two different sizes and weights, we obtained an original acoustic outdoor benchmark dataset at 24 points. The experimentally obtained results revealed that the localization error values were lower for 0∘ and ±45∘ than for ±90∘. Moreover, we demonstrated the relative accuracy for acceptable ranges of tolerance for the obtained localization error values.

Mouse vocal emission and acoustic complexity do not scale linearly with the size of a social group.

Adult mice emit ultrasonic vocalizations (USVs), sounds above the range of human hearing, during social encounters. While mice alter their vocal emissions between isolated and social contexts, technological impediments have hampered our ability to assess how individual mice vocalize in group social settings. We overcame this challenge by implementing an 8-channel microphone array system, allowing us to determine which mouse emitted individual vocalizations across multiple social contexts. This technology, in conjunction with a new approach for extracting and categorizing a complex, full repertoire of vocalizations, facilitated our ability to directly compare how mice modulate their vocal emissions between isolated, dyadic and group social environments. When comparing vocal emission during isolated and social settings, we found that socializing male mice increase the proportion of vocalizations with turning points in frequency modulation and instantaneous jumps in frequency. Moreover, males change the types of vocalizations emitted between social and isolated contexts. In contrast, there was no difference in male vocal emission between dyadic and group social contexts. Female vocal emission, while predominantly absent in isolation, was also similar during dyadic and group interactions. In particular, there were no differences in the proportion of vocalizations with frequency jumps or turning points. Taken together, the findings lay the groundwork necessary for elucidating the stimuli underlying specific features of vocal emission in mice.

Development of an MEMS ultrasonic microphone array system and its application to compressed wavefield imaging of concrete

Although contactless ultrasonic wavefield imaging shows potential for effective nondestructive inspection of various engineering materials, it has been rarely applied to concrete materials owing to technical challenges including low signal-to-noise ratio (SNR) caused by inherent heterogeneity of concrete. This paper presents development of a multi-channel MEMS ultrasonic microphone array system and its application to compressed wavefield imaging of concrete materials. The developed multi-channel MEMS ultrasonic microphone array system contains eight MEMS ultrasonic microphone elements and a signal conditioning circuit that enables measurements of ultrasonic signals with high SNR. A compressed sensing approach, based on the multiple measurement vector (MMV) concept, is applied to reconstruct a full dense ultrasonic wavefield data from sparsely sampled ultrasonic wavefield data. Experiments are carried out on a laboratory concrete sample to verify the performance of the developed MEMS microphone array system and proposed compressed sensing approach and then large-scale concrete samples to demonstrate practical application. The experimental results demonstrate that the developed MEMS microphone array system provides high-quality (SNR > 20 dB) ultrasonic data collected from concrete elements; furthermore, the proposed compressed sensing approach provides accurate reconstruction of dense wavefield data, as determined by peak signal-to-noise ratio (PSNR), from sparsely measured wavefield data with compression ratios up to 85% and PSNR above 25 dB in data collected form realistic large-scale concrete samples. By combining the MEMS array system and compressed sensing approach, the total ultrasonic data acquisition time needed to produce dense wavefield data can be significantly reduced.

A hybrid spiral microphone array design for performance and portability

The logarithmic spiral has become a common design archetype for the placement of microphones in microphone array systems. Such designs tend to perform well; however, when the diameter of the array is increased to improve the array’s angular resolution, the portability and convenience of the array are significantly compromised. Large spiral-based arrays of more than a few meters in diameter are unwieldy to transport and time-consuming to set up once the array has been transported to the test location. The purpose of this investigation is to serve as a proof of concept to establish the anticipated performance of a new hybrid spiral microphone array. This hybrid microphone array design will combine the portability and convenience benefits of smaller spiral array designs with the performance characteristics of larger arrays. Four modified spiral microphone arrays are proposed. The candidate arrays are constructed by placing microphones exclusively on the axes at the points where the spiral geometries intercept the axes. The resulting arrays are modular, enabling the arrays to be quickly dis-assembled, transported, and re-assembled. The candidate array designs are subjected to a battery of angular resolution testing, and the results are compared with standard existing array designs.

Ultrashort-range, high-frequency communication by female mice shapes social interactions

Animals engage in complex social encounters that influence social groups and resource allocation. During these encounters, acoustic signals, used at both short and long ranges, play pivotal roles in regulating the behavior of conspecifics. Mice, for instance, emit ultrasonic vocalizations, signals above the range of human hearing, during close-range social interactions. How these signals shape behavior, however, is unknown due to the difficulty in discerning which mouse in a group is vocalizing. To overcome this impediment, we used an eight-channel microphone array system to determine which mouse emitted individual vocal signals during 30 minutes of unrestrained social interaction between a female and a single male or female conspecific. Females modulated both the timing and context of vocal emission based upon their social partner. Compared to opposite-sex pairings, females in same-sex pairs vocalized when closer to a social partner and later in the 30 minutes of social engagement. Remarkably, we found that female mice exhibited no immediate changes in acceleration (movement) to male-emitted vocal signals. Both males and females, in contrast, modulated their behavior following female-emitted vocal signals in a context-dependent manner. Thus, our results suggest female vocal signals function as a means of ultrashort-range communication that shapes mouse social behavior.

Superhuman Hearing - Virtual Prototyping of Artificial Hearing: a Case Study on Interactions and Acoustic Beamforming.

Directivity and gain in microphone array systems for hearing aids or hearable devices allow users to acoustically enhance the information of a source of interest. This source is usually positioned directly in front. This feature is called acoustic beamforming. The current study aimed to improve users' interactions with beamforming via a virtual prototyping approach in immersive virtual environments (VEs). Eighteen participants took part in experimental sessions composed of a calibration procedure and a selective auditory attention voice-pairing task. Eight concurrent speakers were placed in an anechoic environment in two virtual reality (VR) scenarios. The scenarios were a purely virtual scenario and a realistic 360° audio-visual recording. Participants were asked to find an individual optimal parameterization for three different virtual beamformers: (i) head-guided, (ii) eye gaze-guided, and (iii) a novel interaction technique called dual beamformer, where head-guided is combined with an additional hand-guided beamformer. None of the participants were able to complete the task without a virtual beamformer (i.e., in normal hearing condition) due to the high complexity introduced by the experimental design. However, participants were able to correctly pair all speakers using all three proposed interaction metaphors. Providing superhuman hearing abilities in the form of a dual acoustic beamformer guided by head and hand movements resulted in statistically significant improvements in terms of pairing time, suggesting the task-relevance of interacting with multiple points of interests.

Mapping sources of noise in an intensive care unit.

SummaryExcessive noise in hospitals adversely affects patients’ sleep and recovery, causes stress and fatigue in staff and hampers communication. The World Health Organization suggests sound levels should be limited to 35 decibels. This is probably unachievable in intensive care units, but some reduction from current levels should be possible. A preliminary step would be to identify principal sources of noise. As part of a larger project investigating techniques to reduce environmental noise, we installed a microphone array system in one with four beds in an adult general intensive care unit. This continuously measured locations and sound pressure levels of noise sources. This report summarises results recorded over one year. Data were collected between 7 April 2017 and 16 April 2018 inclusive. Data for a whole day were available for 248 days. The sound location system revealed that the majority of loud sounds originated from extremely limited areas, very close to patients’ ears. This proximity maximises the adverse effects of high environmental noise levels for patients. Some of this was likely to be appropriate communication between the patient, their caring staff and visitors. However, a significant proportion of loud sounds may originate from equipment alarms which are sited at the bedside. A redesign of the intensive care unit environment to move alarm sounds away from the bed‐side might significantly reduce the environmental noise burden to patients.

FPGA based dual microphone speech enhancement

This paper proposes an efficient reconfigurable hardware design of dual microphone speech enhancement technique using sound source localization and multi band spectral subtraction methods with elimination of background noise. Firstly, we have used a time delay of arrival algorithm using phase transform (PHAT) to achieve the time difference between the microphone signals. PHAT based filter can reach high SNR gains, which makes it very suitable for localizing the sound source in a microphone array system. After adjustment of the delay between the signals, multi band spectral subtraction technique enhances the signal from the background noise environment in each of the frequency bands. Our design has been implemented in Spartan6 Lx45 FPGA and we have presented the implementation results in terms of subjective and objective evaluations. We have also compared the angular separation between the microphones to the resultant angle between the microphones and observed that proposed design provides very sharp accuracy in every corresponding angle. The objective and subjective evaluation established that our design provides better throughput compared to the existing state of the art research works. The evaluation infers that our proposed hardware induce feasibility for hand-held devices in background noisy environment.

Development of the application of the digital microphone array system for real time source localization

This research is to develop a digital microphone array system to build a real-time sound source localization system and to produce acoustical holography. Acoustical holography can be understood as taking a photo of sound which can be used to source localization. In the situation of free field with an unknown signal, source signal is restored by time reversal mirror(TRM) where a free-field impulse response function(IRF) is used to achieve the goal of real time source localization. During the processing, the unknown source location is identified by scanning over a possible space for source locations to find a maximum restored signal. In the present study, simulations and experiments of source localization are carried out in 2D and 3D space. In the experiment of source localization with single source, the estimation errors are below 10% in certain distances between source and microphone array. For two sources situation, the distance between two sources will limit the application of the present approach.

Experimental determination of the effects of boundary reflection on the angular resolution of microphone arrays

The Rayleigh criterion has long been considered the standard criterion for angular resolution of imaging systems, including microphone arrays. However, advanced beamforming methods have been developed in the past 20 years that have dramatically improved the angular resolution of microphone array systems. In this investigation, the angular resolution performance of three scaled microphone arrays and one alternative array geometry were tested with both approximately free-field and reflective boundary conditions. All of the arrays were subjected to a thorough regimen of testing with broadband acoustic sources. Beamforming analysis was performed with the Delay-and-Sum, TIDY, DAMAS, DAMAS2, and CLEAN-SC algorithms. The Delay-and-Sum algorithm is shown to offer the lowest angular resolution performance because it does not separate the acoustic source map from the point spread function of the array. The DAMAS algorithm offers the greatest angular resolution because it numerically deconvolutes the acoustic source map from the point spread function. However, deconvolution-based algorithms (DAMAS and DAMAS2) were the most negatively affected by boundary reflection effects. The logarithmic spiral array is shown to offer versatile performance across a wide range of frequencies, while an alternative quasi-periodic array yields results that are highly frequency-dependent. It is demonstrated that this is because of gaps in the source-to-element differences coverage, and the gaps in coverage correspond to half-wavelengths of frequency bands with significantly lower angular resolution performance.

A Robust Real Time Direction-of-Arrival Estimation Method for Sequential Movement Events of Vehicles.

Parameters estimation of sequential movement events of vehicles is facing the challenges of noise interferences and the demands of portable implementation. In this paper, we propose a robust direction-of-arrival (DOA) estimation method for the sequential movement events of vehicles based on a small Micro-Electro-Mechanical System (MEMS) microphone array system. Inspired by the incoherent signal-subspace method (ISM), the method that is proposed in this work employs multiple sub-bands, which are selected from the wideband signals with high magnitude-squared coherence to track moving vehicles in the presence of wind noise. The field test results demonstrate that the proposed method has a better performance in emulating the DOA of a moving vehicle even in the case of severe wind interference than the narrowband multiple signal classification (MUSIC) method, the sub-band DOA estimation method, and the classical two-sided correlation transformation (TCT) method.