Human Localization Performance Research Articles

Accounting for individual differences in the effects of hearing protectors on sound source localization

Modern hearing protection devices (HPDs) mitigate the risk of noise-induced hearing loss when used as intended, but negative auditory perceptual side-effects continue to limit usability in critical settings. Dozens of studies, including previous studies by our group, have shown that HPDs lead to significant errors in sound source localization, including large errors in source elevation perception and disorienting front-back confusions. Degradation of performance relative to open-ear listening arises due to peripheral disruptions of monaural and binaural acoustic cues for sound localization; for higher-attenuation devices, reduced audibility can also limit access to these cues, even if cues are relatively intact. A recent multi-site effort by our group leveraged manikin-based acoustic measurements of HPD-induced signal distortions to predict human localization performance during HPD use. Manikin-based acoustic metrics were positively correlated with behavioral performance across a large population of human listeners (n ≥ 120), enabling discrimination of localization impacts across HPDs, but significant individual variability was evident. Here we consider individual factors that may contribute to variability in HPD localization impact across wearers, including audiometric factors and auricular/acoustic factors. Correlational analyses of individualized predictors with localization performance provide new insight on factors that may differentially constrain – or facilitate – sound localization during HPD use.

A Measure Based on Beamforming Power for Evaluation of Sound Field Reproduction Performance

This paper proposes a measure to evaluate sound field reproduction systems with an array of loudspeakers. The spatially-averaged squared error of the sound pressure between the desired and the reproduced field, namely the spatial error, has been widely used, which has considerable problems in two conditions. First, in non-anechoic conditions, room reflections substantially deteriorate the spatial error, although these room reflections affect human localization to a lesser degree. Second, for 2.5-dimensional reproduction of spherical waves, the spatial error increases consistently due to the difference in the amplitude decay rate, whereas the degradation of human localization performance is limited. The measure proposed in this study is based on the beamforming powers of the desired and the reproduced fields. Simulation and experimental results show that the proposed measure is less sensitive to room reflections and the amplitude decay than the spatial error, which is likely to agree better with the human perception of source localization.

A high-resolution head-related transfer function dataset and 3D ear model database

Binaural reproduction techniques, which use head-related transfer functions (HRTFs), become more and more popular. Human localization performance using binaural synthesis is, however, often poor due to non-individual HRTFs. To investigate the physical relationship between the ear geometry and the directional HRTFs, the ears and the HRTF datasets of 48 subjects are measured. The detailed ear models are obtained from magnetic resonance imaging scans of the subjects. Two rough scans series of the head and a detailed horizontal scan series, which covers both ears, are taken. The 3D model meshes, which are generated from the MRI scans, allow a very precise determination of anthropometric dimensions which can be used for the individualization of the HRTFs. Additionally, the relationship between the anthropometric dimensions and monaural cues of the HRTFs is studied by the boundary element method. These simulations show which parts of the pinna are involved in case of resonances or destructive interferences.

On the localization of complex sounds: temporal encoding based on input-slope coincidence detection of envelopes.

Behavioral and neural findings demonstrate that animals can locate low-frequency sounds along the azimuth by detecting microsecond interaural time differences (ITDs). Information about ITDs is also available in the amplitude modulations (i.e., envelope) of high-frequency sounds. Since medial superior olivary (MSO) neurons encode low-frequency ITDs, we asked whether they employ a similar mechanism to process envelope ITDs with high-frequency carriers, and the effectiveness of this mechanism compared with the process of low-frequency sound. We developed a novel hybrid in vitro dynamic-clamp approach, which enabled us to mimic synaptic input to brain-slice neurons in response to virtual sound and to create conditions that cannot be achieved naturally but are useful for testing our hypotheses. For each simulated ear, a virtual sound, computer generated, was used as input to a computational auditory-nerve model. Model spike times were converted into synaptic input for MSO neurons, and ITD tuning curves were derived for several virtual-sound conditions: low-frequency pure tones, high-frequency tones modulated with two types of envelope, and speech sequences. Computational models were used to verify the physiological findings and explain the biophysical mechanism underlying the observed ITD coding. Both recordings and simulations indicate that MSO neurons are sensitive to ITDs carried by spectrotemporally complex virtual sounds, including speech tokens. Our findings strongly suggest that MSO neurons can encode ITDs across a broad-frequency spectrum using an input-slope-based coincidence-detection mechanism. Our data also provide an explanation at the cellular level for human localization performance involving high-frequency sound described by previous investigators.

An ideal-observer model of human sound localization

In recent years, a great deal of research within the field of sound localization has been aimed at finding the acoustic cues that human listeners use to localize sounds and understanding the mechanisms by which they process these cues. In this paper, we propose a complementary approach by constructing an ideal-observer model, by which we mean a model that performs optimal information processing within a Bayesian context. The model considers all available spatial information contained within the acoustic signals encoded by each ear. Parameters for the optimal Bayesian model are determined based on psychoacoustic discrimination experiments on interaural time difference and sound intensity. Without regard as to how the human auditory system actually processes information, we examine the best possible localization performance that could be achieved based only on analysis of the input information, given the constraints of the normal auditory system. We show that the model performance is generally in good agreement with the actual human localization performance, as assessed in a meta-analysis of many localization experiments (Best et al. in Principles and applications of spatial hearing, pp 14-23. World Scientific Publishing, Singapore, 2011). We believe this approach can shed new light on the optimality (or otherwise) of human sound localization, especially with regard to the level of uncertainty in the input information. Moreover, the proposed model allows one to study the relative importance of various (combinations of) acoustic cues for spatial localization and enables a prediction of which cues are most informative and therefore likely to be used by humans in various circumstances.

Real-world application of auditory models to hearing instrument design.

Auditory models provide a powerful tool for designing and developing signal processing algorithms of modern digital hearing instruments and can even be integrated directly into these algorithms. Models for loudness perception have been applied directly in hearing instrument algorithms with two applications: to control the gain of a hearing instrument and to limit the maximum output power of a hearing instrument as a “loudness limiter.” Another example is the application of a very simple model in a hearing instrument to help resolve localization problems due to the microphone position in BTE hearing instruments, resulting in reduced front/back confusions. Examples of the application of models to the development and analysis of hearing instrument performance in real-life environments include the use of auditory scene analysis models to better understand human sound source classification and to improve the performance of automatic control systems in hearing instruments. A last example is the application of models describing human localization performance under realistic acoustic environments to understand the impact that hearing instrument signal processing has on the ability of hearing impaired people to localize sounds with hearing instruments. This talk will explore and discuss the potential of these different approaches for hearing instrument technology.

Auditory evoked magnetic fields in relation to interaural time delay and interaural correlation

The detection of interaural time differences (ITD) for sound localization depends on the similarity between the left and right ear signals, namely interaural correlation (IAC). Human localization performance deteriorates with decreasing IACs. In order to examine activity related to localization performance in the human cortex, auditory evoked magnetic fields to the ITD of bandpass noises with different IACs were analyzed. When the IAC was 0.95, the N1m amplitudes, i.e., the estimated equivalent current dipole moments, increased with increasing ITD. However the effect of ITD on the N1m amplitudes was not significant when the IAC was 0.5. When the ITD was 0.7 ms, the N1m amplitudes decreased with decreasing IACs. There were no systematic changes in the source location of N1m in the auditory cortex related to changes in ITD or IAC. The results suggest that localization performance is reflected in N1m amplitudes.

Using a combined localization/detection model to simulate human localization performance near the masked detection threshold level

Recently, the perceptual lateralization of a partly masked target has been successfully simulated using the interaural cross-correlation difference (ICCD) model [Braasch, J. Acoust. Soc. Am. 108, 2597 (2000)]. However, in the accompanying listening tests, the target level was often found to be below the masked detection threshold level. To improve the model performance, a detection threshold model has been implemented in the localization model so that the localization process is triggered only when the target level is above a threshold. Otherwise, the position of the sound source is determined according to a behavioral pattern. The detection stage is based on an on- and offset detection algorithm that analyzes the derivative in time. For the simulation of the binaural conditions, the equalization-cancellation algorithm of Durlach [J. Acoust. Soc. Am. 35, 1206–1218 (1963)] has been included in the model. It has been shown that for target levels above the masked detection threshold, the on-/offset detection algorithm is accurate enough to trigger the subtraction process of the ICCD algorithm. Furthermore, the improved model has resulted in better simulations of human localization patterns in the presence of a distracting sound.

Auditory localization of a nearby point source

Although human auditory localization has been studied extensively in the past century, little is known about the localization of nearby sound sources. The head-related transfer function (HRTF) contains all relevant localization information and has been thoroughly examined for relatively distant sources, but may exhibit unique properties in the ‘‘near-field’’ region within 1 m of the center of the head. A rigid-sphere computational model of the head has been used to estimate near-field HRTFs, and a KEMAR manikin and a specialized acoustic ‘‘point’’ source have been used to measure HRTFs for sources as close as 0.25 m. For a fixed source direction, the interaural time delay is roughly independent of distance, but the interaural amplitude difference increases dramatically as the source approaches within 1 m of the head. When the source is near one ear, the interaural amplitude difference exceeds 20 dB across the audio spectrum. The differences between near-field and more distal HRTFs will be discussed, including comments on how near-field effects may facilitate three-dimensional localization judgments. In addition, preliminary results of a psychoacoustic experiment designed to measure human localization performance for sources within ‘‘arm’s reach’’ of the listener may be presented. [Work supported by AFOSR and NIDCD].