Dynamic binaural sound localization based on variations of interaural time delays and system rotations

Gaussian Process Regression for Single-Channel Sound Source Localization System Based on Homomorphic Deconvolution

To extract the phase information from multiple receivers, the conventional sound source localization system involves substantial complexity in software and hardware. Along with the algorithm complexity, the dedicated communication channel and individual analog-to-digital conversions prevent an increase in the system's capability due to feasibility. The previous study suggested and verified the single-channel sound source localization system, which aggregates the receivers on the single analog network for the single digital converter. This paper proposes the improved algorithm for the single-channel sound source localization system based on the Gaussian process regression with the novel feature extraction method. The proposed system consists of three computational stages: homomorphic deconvolution, feature extraction, and Gaussian process regression in cascade. The individual stages represent time delay extraction, data arrangement, and machine prediction, respectively. The optimal receiver configuration for the three-receiver structure is derived from the novel similarity matrix analysis based on the time delay pattern diversity. The simulations and experiments present precise predictions with proper model order and ensemble average length. The nonparametric method, with the rational quadratic kernel, shows consistent performance on trained angles. The Steiglitz-McBride model with the exponential kernel delivers the best predictions for trained and untrained angles with low bias and low variance in statistics.

Ultrasonic Sound Guide System with Eyeglass Device for the Visually Impaired

The ultrasonic sound guide system presents the audio broadcasting system based on the inaudible ultrasonic sound to assist the indoor and outdoor navigation of the visually impaired. The transmitters are placed at the point of interest to propagate the frequency modulated voice signal in ultrasonic sound range. The dual channel receiver device is carried by the visually impaired person in the form of eyeglasses to receive the ultrasonic sound for the voice signal via demodulation. Since the ultrasonic sound demonstrates the acoustic properties, the velocity, directivity, attenuation, and superposition of ultrasonic sound provide the acoustic clue to the user for localizing the multiple transmitter positions by binaural localization capability. The visually impaired hear the designated voice signal and follow the signal attributions to arrive at the specific location. Due to the low microphone gain from side addressing, the time delay between the receiver channels demonstrates the high variance and high bias in end directions. However, the perception experiment shows the further prediction accuracy in end directions as compared to the center direction outcomes. The overall evaluations show the precise directional prediction for narrow- and wide-angle situations. The ultrasonic sound guide system is a useful device to localize places in the near field without touching braille.

Measuring threshold and latency of motion perception on a swinging bed

INTRODUCTION

Our objective was to develop and to evaluate a system to measure latency and threshold of pendular motion perception based on a swinging bed.

MATERIALS AND METHODS

This prospective study included 30 healthy adults (age: 32 ± 12 years). All subjects were tested twice with a 10 min. interval. A second trial was conducted 2 to 15 days after. A rehabilitation swinging bed was connected to an electronic device emitting a beep at the beginning of each oscillation phase with an adjustable time lag. Subjects were blindfolded and auditory cues other than the beep were minimized. The acceleration threshold was measured by letting the bed oscillate freely until a natural break and asking the patient when he did not perceive any motion. The perception latency was determined by asking the patient to indicate whether the beep and the peak of each oscillation were synchronous. The time lag between sound and peak of the head position was swept from -750 to +750 ms by 50 ms increments.

RESULTS

The mean acceleration threshold was 9.2±4.60 cm/s2. The range width of the synchronous perception interval was estimated as 535±190 ms. The point of subjective synchronicity defined as the center of this interval was -195±106 ms (n = 30). The test-retest evaluation in the same trial showed an acceptable reproducibility for the acceleration threshold and good to excellent for all parameters related to sound-movement latency.

CONCLUSION

Swinging bed combined to sound stimulation can provide reproducible information on movement perception in a simple and non-invasive manner with highly reproducible results.

Single-Channel Multiple-Receiver Sound Source Localization System with Homomorphic Deconvolution and Linear Regression

The conventional sound source localization systems require the significant complexity because of multiple synchronized analog-to-digital conversion channels as well as the scalable algorithms. This paper proposes a single-channel sound localization system for transport with multiple receivers. The individual receivers are connected by the single analog microphone network which provides the superimposed signal over simple connectivity based on asynchronized analog circuit. The proposed system consists of two computational stages as homomorphic deconvolution and machine learning stage. A previous study has verified the performance of time-of-flight estimation by utilizing the non-parametric and parametric homomorphic deconvolution algorithms. This paper employs the linear regression with supervised learning for angle-of-arrival prediction. Among the circular configurations of receiver positions, the optimal location is selected for three-receiver structure based on the extensive simulations. The non-parametric method presents the consistent performance and Yule–Walker parametric algorithm indicates the least accuracy. The Steiglitz–McBride parametric algorithm delivers the best predictions with reduced model order as well as other parameter values. The experiments in the anechoic chamber demonstrate the accurate predictions in proper ensemble length and model order.

Speech Envelope Dynamics for Noise-Robust Auditory Scene Analysis in Robotics

Humans make extensive use of auditory cues to interact with other humans, especially in challenging real-world acoustic environments. Multiple distinct acoustic events usually mix together in a complex auditory scene. The ability to separate and localize mixed sound in complex auditory scenes remains a demanding skill for binaural robots. In fact, binaural robots are required to disambiguate and interpret the environmental scene with only two sensors. At the same time, robots that interact with humans should be able to gain insights about the speakers in the environment, such as how many speakers are present and where they are located. For this reason, the speech signal is distinctly important among auditory stimuli commonly found in human-centered acoustic environments. In this paper, we propose a Bayesian method of selectively processing acoustic data that exploits the characteristic amplitude envelope dynamics of human speech to infer the location of speakers in the complex auditory scene. The goal was to demonstrate the effectiveness of this speech-specific temporal dynamics approach. Further, we measure how effective this method is in comparison with more traditional methods based on amplitude detection only.

Wearable Hearing Assist System to Provide Hearing-Dog Functionality

This study developed a wearable hearing-assist system that can identify the direction of a sound source while using short-term interaural time differences (ITDs) of sound pressure and convey the sound source direction to a hearing-impaired person via vibrators that are attached to his or her shoulders. This system, which is equipped with two microphones, could dynamically detect and convey the direction of front, side, and even rear sound sources. A male subject was able to turn his head toward continuous or intermittent sound sources within approximately 2.8 s when wearing the developed system. The sound source direction is probably overestimated when the interval between the two ears is smaller. When the subject can utilize vision, this may help in tracking the location of the target sound source, especially if the target comes into view, and it may shorten the tracking period.

A Bayesian computational basis for auditory selective attention using head rotation and the interaural time-difference cue

The process of resolving mixtures of several sounds into their separate individual streams is known as auditory scene analysis and it remains a challenging task for computational systems. It is well-known that animals use binaural differences in arrival time and intensity at the two ears to find the arrival angle of sounds in the azimuthal plane, and this localization function has sometimes been considered sufficient to enable the un-mixing of complex scenes. However, the ability of such systems to resolve distinct sound sources in both space and frequency remains limited. The neural computations for detecting interaural time difference (ITD) have been well studied and have served as the inspiration for computational auditory scene analysis systems, however a crucial limitation of ITD models is that they produce ambiguous or "phantom" images in the scene. This has been thought to limit their usefulness at frequencies above about 1khz in humans. We present a simple Bayesian model and an implementation on a robot that uses ITD information recursively. The model makes use of head rotations to show that ITD information is sufficient to unambiguously resolve sound sources in both space and frequency. Contrary to commonly held assumptions about sound localization, we show that the ITD cue used with high-frequency sound can provide accurate and unambiguous localization and resolution of competing sounds. Our findings suggest that an "active hearing" approach could be useful in robotic systems that operate in natural, noisy settings. We also suggest that neurophysiological models of sound localization in animals could benefit from revision to include the influence of top-down memory and sensorimotor integration across head rotations.