Sound Source Localization Accuracy Research Articles

A data complementary method for sound source localization based on four-element microphone array groups

Data loss or distortion has adverse effects on sound source localization (SSL) accuracy and stability. Based on the sound source azimuth estimation algorithm, this paper establishes a model of a single four-element main microphone array, and proposes a data complementary method of SSL. The calculation formula of sound source coordinates is derived from the main array. Then, the effectiveness of the proposed algorithm is verified by the study of array parameters. Besides the sound velocity and elevation angle, the array parameters also include the distance between two array elements. Array groups are established surrounding the main array on the horizontal plane, through which the localization data are collected and complementarily processed, so as to relocate the sound source. The results show that the coordinate error rate against the theoretical data is approximately 5% and the error rate of the angle is approximately 0.5%. The SSL efficiency is well guaranteed.

Sound Localization Bias and Error in Bimodal Listeners Improve Instantaneously When the Device Delay Mismatch Is Reduced.

Users of a cochlear implant (CI) in one ear, who are provided with a hearing aid (HA) in the contralateral ear, so-called bimodal listeners, are typically affected by a constant and relatively large interaural time delay offset due to differences in signal processing and differences in stimulation. For HA stimulation, the cochlear travelling wave delay is added to the processing delay, while for CI stimulation, the auditory nerve fibers are stimulated directly. In case of MED-EL CI systems in combination with different HA types, the CI stimulation precedes the acoustic HA stimulation by 3 to 10 ms. A self-designed, battery-powered, portable, and programmable delay line was applied to the CI to reduce the device delay mismatch in nine bimodal listeners. We used an A-B-B-A test design and determined if sound source localization improves when the device delay mismatch is reduced by delaying the CI stimulation by the HA processing delay (τHA). Results revealed that every subject in our group of nine bimodal listeners benefited from the approach. The root-mean-square error of sound localization improved significantly from 52.6° to 37.9°. The signed bias also improved significantly from 25.2° to 10.5°, with positive values indicating a bias toward the CI. Furthermore, two other delay values (τHA –1 ms and τHA +1 ms) were applied, and with the latter value, the signed bias was further reduced in some test subjects. We conclude that sound source localization accuracy in bimodal listeners improves instantaneously and sustainably when the device delay mismatch is reduced.

Improving the resolution of underwater acoustic image measurement by deconvolution

The conventional beamforming (CBF) map of underwater acoustic image measurement can be expressed as a convolution of the source distribution and the response of the beamformer to a point source, defined as the beam pattern or the point spread function (PSF). By deconvolving the CBF beamformer’s map, the distribution of the actual sources with a clean beam map can be obtained to improve the resolution. In this paper, the deconvolved conventional beamforming (dCv) is applied to underwater acoustic image measurement to improve the accuracy of sound source localization. Due to the point spread function of the array in near field is dependent on the focused point, which means that the PSF is shift variant, so it is necessary to use shift-variant deconvolution method. In this paper, an extended Richardson-Lucy (Ex-RL) algorithm is applied to the two-dimensional shift-variant deconvolution acoustic image measurement problem to improve resolution. The method is compared with the original-RL, classical deconvolution approach for the mapping of acoustic sources (DAMAS) and non-negative least squares (NNLS). The simulation and the experiment results verify the effectiveness of the algorithm.

A fusion algorithm of passive sound source localization based on the two-plane four-element cross array

In this work, a fusion algorithm is proposed for improving the accuracy and stability of passive sound source localization. Different from the traditional algorithm that contains a single-plane cross array, here, the fusion algorithm is used to overcome the position blur in the process of localization. First, the two-plane four-element cross array model is established. Based on this model, the method is defined to judge the position where the sound source is located. According to the localization principle, we derive the calculation formula of the sound source position, based on a single four-element planar array. Then, the elevation angle sine value is introduced into the coordinate formula as the weighted coefficient by analyzing the indirect measurement error, and the fusion algorithm is employed to conduct the sound source localization, based on the two-plane four-element cross array. Finally, the relationships are obtained, between the time delay estimation error, the elevation angle, the horizontal angle, and the localization performance. Besides, the validity of this algorithm is validated by measuring the ranging and direction-finding accuracy. The results show that the distance error rate is within 2%, and the angle error rate is within 3%, which means a good localization effect. The proposed algorithm is expected to be widely used in thunderstorm cloud detection for its quick measurement and high precision.

Arbitrary Microphone Array Optimization Method Based on TDOA for Specific Localization Scenarios.

Various microphone array geometries (e.g., linear, circular, square, cubic, spherical, etc.) have been used to improve the positioning accuracy of sound source localization. However, whether these array structures are optimal for various specific localization scenarios is still a subject of debate. This paper addresses a microphone array optimization method for sound source localization based on TDOA (time difference of arrival). The geometric structure of the microphone array is established in parametric form. A triangulation method with TDOA was used to build the spatial sound source location model, which consists of a group of nonlinear multivariate equations. Through reasonable transformation, the nonlinear multivariate equations can be converted to a group of linear equations that can be approximately solved by the weighted least square method. Then, an optimization model based on particle swarm optimization (PSO) algorithm was constructed to optimize the geometric parameters of the microphone array under different localization scenarios combined with the spatial sound source localization model. In the optimization model, a reasonable fitness evaluation function is established which can comprehensively consider the positioning accuracy and robustness of the microphone array. In order to verify the array optimization method, two specific localization scenarios and two array optimization strategies for each localization scenario were constructed. The optimal array structure parameters were obtained through numerical iteration simulation. The localization performance of the optimal array structures obtained by the method proposed in this paper was compared with the optimal structures proposed in the literature as well as with random array structures. The simulation results show that the optimized array structure gave better positioning accuracy and robustness under both specific localization scenarios. The optimization model proposed could solve the problem of array geometric structure design based on TDOA and could achieve the customization of microphone array structures under different specific localization scenarios.

Azimuthal sound source localization of various sound stimuli under different conditions

AimTo evaluate azimuthal sound-source localization performance under different conditions, with a view to optimizing a routine sound localization protocol. Material and methodTwo groups of healthy, normal-hearing subjects were tested identically, except that one had to keep their head still while the other was allowed to turn it. Sound localization was tested without and then with a right ear plug (acute auditory asymmetry) for each of the following sound stimuli: pulsed narrow-band centered on 250Hz, continuous narrowband centered on 2000Hz, 4000Hz and 8000Hz, continuous 4000Hz warble, pulsed white noise, and word (“lac” (lake)). Root mean square error was used to calculate sound-source localization accuracy. ResultsWith fixed head, localization was significantly disturbed by the earplug for all stimuli (P<0.05). The most discriminating stimulus was continuous 4000Hz narrow-band: area under the ROC curve (AUC), 0.99 [95% CI, 0.95–1.01] for screening and 0.85 [0.82–0.89] for diagnosis. With mobile head, localization was significantly better than with fixed head for 4000 and 8000Hz stimuli (P<0.05). The most discriminating stimulus was continuous 2000Hz narrow-band: AUC, 0.90 [0.83–0.97] for screening and 0.75 [0.71–0.79] for diagnosis. In both conditions, pulsed noise (250Hz narrow-band, white noise or word) was less difficult to localize than continuous noise. ConclusionThe test was more sensitive with the head immobile. Continuous narrow-band stimulation centered on 4000Hz most effectively explored interaural level difference. Pulsed narrow-band stimulation centered on 250Hz most effectively explored interaural time difference. Testing with mobile head, closer to real-life conditions, was most effective with continuous narrow-band stimulation centered on 2000Hz.

Auditory localization accuracy and auditory spatial discrimination in children with auditory processing disorders

The present study investigated spatial hearing in children aged 6–12 years diagnosed with Auditory Processing Disorders (APD) and compared their results to those of a group of control children matched in age. Sound source localization accuracy was quantified using an absolute localization task and sound source discrimination by measuring the minimum audible angle. Low- and high-frequency noise bursts were presented from eight loudspeaker positions in the left and right hemifields (0°, 30, 60°, and 90° azimuth). Median absolute localization accuracy did not differ between children with APD and control children. However, the intra-individual variability of pointing behavior was higher for children with APD. In contrast, children with APD had significantly higher minimum audible angle thresholds than control children. These findings show that APD impairs sound source discrimination, but does not affect the median relationship between actual and judged sound source locations.

Acoustic SLAM

An algorithm is presented that enables devices equipped with microphones, such as robots, to move within their environment in order to explore, adapt to, and interact with sound sources of interest. Acoustic scene mapping creates a three-dimensional (3D) representation of the positional information of sound sources across time and space. In practice, positional source information is only provided by Direction-of-Arrival (DoA) estimates of the source directions; the source-sensor range is typically difficult to obtain. DoA estimates are also adversely affected by reverberation, noise, and interference, leading to errors in source location estimation and consequent false DoA estimates. Moreover, many acoustic sources, such as human talkers, are not continuously active, such that periods of inactivity lead to missing DoA estimates. Withal, the DoA estimates are specified relative to the observer's sensor location and orientation. Accurate positional information about the observer therefore is crucial. This paper proposes Acoustic Simultaneous Localization and Mapping (aSLAM), which uses acoustic signals to simultaneously map the 3D positions of multiple sound sources while passively localizing the observer within the scene map. The performance of aSLAM is analyzed and evaluated using a series of realistic simulations. Results are presented to show the impact of the observer motion and sound source localization accuracy.

Changes in sound-source localization for children with bilateral severe to profound hearing loss following simultaneous bilateral cochlear implantation

Background: Sound localization is a valuable skill that children can develop to some extent via bilateral cochlear implants (biCIs). However, little is known regarding the change that can be expected in sound-source localization accuracy (SLA) pre- and post-biCI for children with bilateral, severe-to-profound hearing impairment who spent their early years listening via bilateral hearing aids (biHAs). This study therefore aimed to prospectively assess SLA in a group of children before, and at one year after, receiving simultaneous biCIs.Methods: Ten children aged 5–18 years were tested. SLA was assessed using loudspeakers positioned at −60, −30, 0, +30, and +60 degrees azimuth. Root mean square (RMS) errors and percentage correct scores were calculated. Changes in SLA were analysed via paired t-tests and potential relationships between hearing threshold levels (HTLs) and SLA via correlation analyses. Response distributions via biHAs and biCIs were examined via scatterplots.Results: The mean within-subject changes in SLA were a significant improvement in RMS error of 11.9° (p < 0.05) and in per cent correct by 21.5% (p < 0.05). Scatterplots demonstrated a trend towards better localization of sounds from 0° azimuth via biCIs compared to via biHAs. No significant associations were found between any measures of SLA and HTLs.Conclusions: The findings of the present study demonstrate that simultaneous biCIs lead to improved sound localization in children with bilateral, severe to profound sensorineural hearing loss who previously used biHAs. SLA via biHAs or biCIs could not be predicted from children’s audiograms, and therefore should be measured directly.

Speech Understanding and Sound Source Localization by Cochlear Implant Listeners Using a Pinna-Effect Imitating Microphone and an Adaptive Beamformer.

Sentence understanding scores for patients with cochlear implants (CIs) when tested in quiet are relatively high. However, sentence understanding scores for patients with CIs plummet with the addition of noise. To assess, for patients with CIs (MED-EL), (1) the value to speech understanding of two new, noise-reducing microphone settings and (2) the effect of the microphone settings on sound source localization. Single-subject, repeated measures design. For tests of speech understanding, repeated measures on (1) number of CIs (one, two), (2) microphone type (omni, natural, adaptive beamformer), and (3) type of noise (restaurant, cocktail party). For sound source localization, repeated measures on type of signal (low-pass [LP], high-pass [HP], broadband noise). Ten listeners, ranging in age from 48 to 83 yr (mean = 57 yr), participated in this prospective study. Speech understanding was assessed in two noise environments using monaural and bilateral CIs fit with three microphone types. Sound source localization was assessed using three microphone types. In Experiment 1, sentence understanding scores (in terms of percent words correct) were obtained in quiet and in noise. For each patient, noise was first added to the signal to drive performance off of the ceiling in the bilateral CI-omni microphone condition. The other conditions were then administered at that signal-to-noise ratio in quasi-random order. In Experiment 2, sound source localization accuracy was assessed for three signal types using a 13-loudspeaker array over a 180° arc. The dependent measure was root-mean-score error. Both the natural and adaptive microphone settings significantly improved speech understanding in the two noise environments. The magnitude of the improvement varied between 16 and 19 percentage points for tests conducted in the restaurant environment and between 19 and 36 percentage points for tests conducted in the cocktail party environment. In the restaurant and cocktail party environments, both the natural and adaptive settings, when implemented on a single CI, allowed scores that were as good as, or better, than scores in the bilateral omni test condition. Sound source localization accuracy was unaltered by either the natural or adaptive settings for LP, HP, or wideband noise stimuli. The data support the use of the natural microphone setting as a default setting. The natural setting (1) provides better speech understanding in noise than the omni setting, (2) does not impair sound source localization, and (3) retains low-frequency sensitivity to signals from the rear. Moreover, bilateral CIs equipped with adaptive beamforming technology can engender speech understanding scores in noise that fall only a little short of scores for a single CI in quiet.

Role of expectancy in front-back confusions during sound source localization

Front-back confusions (FBCs) often occur in laboratory experiments. Stimulus complexity, especially for high-frequency sounds, and head motion significantly reduce FBCs, so that in the everyday world FBCs probably do not often influence sound source localization. There is a small literature suggesting that listeners “expectancies” (based on experience or other sensory inputs) for where sound sources might be also affect FBCs. A low-pass noise that produces a large number of FBCs and a high-pass noise that does not were used. Listeners indicated the location of sound sources on the azimuth plane. The study aimed to investigate FBCs and not sound source localization accuracy. For one condition, listeners were told that the noises would all be coming from in front, that in another condition from in back, and in a third condition from the full 360° azimuth circle. In the first (front) and second (back) conditions, most of the sounds came from the front or back respectfully, but 20% did not. The expectancy that sounds would be in front or in back had a large influence on FBCs as compared to when sounds were presented from the entire azimuth circle. (Work supported by grants from NIDCD and Oculus VR, LLC.)

Exploiting Partial Reconfiguration through PCIe for a Microphone Array Network Emulator

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.

Research of Acoustic Source Localization Technology Based On Spatial Time Delay Estimation and Intelligent Signal Analysis

The accurate and real-time localization of sound sources is the basis of machine intelligent technology and industrial and civilian positioning applications. It can provide basic help for many applications. In this paper, first, we investigate the applicability of the generalized cross correlation (GCC) delay estimation algorithm. Secondly, we analyze and study the method of acoustic source localization for the microphone array and design a unique spatial structure. Finally, the embedded system and the human-computer interaction interface are designed to collect and analyze the data so as to obtain the accurate and real-time location of the sound source.

Gaussian filter for TDOA based sound source localization in multimedia surveillance

Although multimedia surveillance systems are becoming increasingly ubiquitous in our living environment, automated multimedia surveillance systems based on video camera lacks the robustness and reliability most of the time in several real applications. To overcome this drawback, audio sensory devices have been taken into account in a considerable amount of research. For example, Sound Source Localization (SSL) may indicate potential security risks and could point the camera in that direction. In this paper, a reliable sound source localization based on Time-Difference-Of-Arrival (TDOA) is explored. The novel aspect of our approach includes a TDOA based Gaussian filter to improve the accuracy and stability of sound source localization. The advantage of our proposed algorithm is its extensive integration with various TDOA-based methods in all kinds of microphone array. The Experimental comparison shows significant improvement over the state of the art TDOA-based algorithm.

Object based approach for electronic variable acoustics systems

Demand for spatially accurate high-quality sound reproduction in the audio entertainment industry is now at an entirely new level. In today’s world of immersive entertainment, sound reproduction is about more than just decibels—via the accurate localization of sound sources, performances can be immeasurably enhanced in classical concerts, operas, theatres, and every field of live entertainment. The days of two-dimensional PAs are over—a new era has arrived with 3D spatial sound and enhanced room acoustics. This paper describes a fully object-based approach to immersive sound reproduction, combining 3D positioning of audio sources and acoustic enhancement on the same unit by processing room reflections as audio objects. The algorithms combine the flexibility of traditional in-line digital reverberation devices with the quality and natural impression of a regenerative reverberation. The result of this process is a subset of discrete, early and late reverberant reflections which are convolved with the direct sound to serve as input objects for further processing. This unique object based system approach offers many advantages with respect to the traditional channel based approach. The technological principles of this approach, along with the results of successful applications throughout Europe, will be shown.

Sound source localization identification procedures: Accuracy, precision, confusions, and misses

Rakerd and Hartmann (1987) provided a useful set of equations that can describe listener performance in sound source localization identification tasks requiring listeners to identify which loudspeaker presented a sound. The data from such identification tasks can be presented in confusion matrices in which one dimension is the actual sound source locations and the other dimension is the reported/perceived sound source locations. This presentation describes how Rakerd and Hartmann’s measures relate to estimates of sound source localization accuracy, precision, confusions, and misses. We will describe some of the advantages and limitations of these measures of performance in sound source localization identification tasks, especially in conditions involving sound sources located around an entire azimuth circle. [Partially support by a grant from the National Institute on Deafness and Other Communication Disorders, NIDCD.]

Compressing Sensing Based Source Localization for Controlled Acoustic Signals Using Distributed Microphone Arrays

In order to enhance the accuracy of sound source localization in noisy and reverberant environments, this paper proposes an adaptive sound source localization method based on distributed microphone arrays. Since sound sources lie at a few points in the discrete spatial domain, our method can exploit this inherent sparsity to convert the localization problem into a sparse recovery problem based on the compressive sensing (CS) theory. In this method, a two-step discrete cosine transform- (DCT-) based feature extraction approach is utilized to cover both short-time and long-time properties of acoustic signals and reduce the dimensions of the sparse model. In addition, an online dictionary learning (DL) method is used to adjust the dictionary for matching the changes of audio signals, and then the sparse solution could better represent location estimations. Moreover, we propose an improved block-sparse reconstruction algorithm using approximate l0 norm minimization to enhance reconstruction performance for sparse signals in low signal-noise ratio (SNR) conditions. The effectiveness of the proposed scheme is demonstrated by simulation results and experimental results where substantial improvement for localization performance can be obtained in the noisy and reverberant conditions.

Design Considerations When Accelerating an FPGA-Based Digital Microphone Array for Sound-Source Localization

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.

Front-back sound source localization confusions when sources and listeners are rotated

Sound source localization identification judgments were made in the azimuth plane with the goal of determining front-back and back-front confusions. The sounds were filtered 125-ms noise bursts: two and 1/10th octave wide at center frequencies of 500 and 4000 Hz, and a wideband (125-8000 Hz) condition. Sounds were either presented from one of six evenly spaced (60o) random loudspeaker locations (random) or the sound presentation rotated clockwise (rotating) around the six loudspeaker array except on 20% of the trials when the location of the loudspeaker was randomly determined. Four conditions were tested: Listener Stationary with Eyes Open (L-O), Listener Stationary with Eyes Closed (L-C), Listener Rotating with Eyes Open (R-O), and Listener Rotating with Eyes Closed (R-C). Listener rotation was clockwise at 45o/s. Localization accuracy and the type of errors, especially front-back and back-front errors, were determined for 18 normal hearing listeners. Sound source localization accuracy and the number of...

Using ILD or ITD Cues for Sound Source Localization and Speech Understanding in a Complex Listening Environment by Listeners With Bilateral and With Hearing-Preservation Cochlear Implants.

To assess the role of interaural time differences and interaural level differences in (a) sound-source localization, and (b) speech understanding in a cocktail party listening environment for listeners with bilateral cochlear implants (CIs) and for listeners with hearing-preservation CIs. Eleven bilateral listeners with MED-EL (Durham, NC) CIs and 8 listeners with hearing-preservation CIs with symmetrical low frequency, acoustic hearing using the MED-EL or Cochlear device were evaluated using 2 tests designed to task binaural hearing, localization, and a simulated cocktail party. Access to interaural cues for localization was constrained by the use of low-pass, high-pass, and wideband noise stimuli. Sound-source localization accuracy for listeners with bilateral CIs in response to the high-pass noise stimulus and sound-source localization accuracy for the listeners with hearing-preservation CIs in response to the low-pass noise stimulus did not differ significantly. Speech understanding in a cocktail party listening environment improved for all listeners when interaural cues, either interaural time difference or interaural level difference, were available. The findings of the current study indicate that similar degrees of benefit to sound-source localization and speech understanding in complex listening environments are possible with 2 very different rehabilitation strategies: the provision of bilateral CIs and the preservation of hearing.