Regularization Approaches for Synthesizing HRTF Directivity Patterns

Estimation of the category of notch frequency bins of the individual head-related transfer functions using the anthropometry of the listener’s pinnae

Efficient prediction of individual head-related transfer functions based on 3D meshes

Four head-related transfer function (HRTF) data sets were compared to determine the effect of HRTF measurement methodology on the localization of spatialized auditory stimuli. Spatial audio interfaces typically require HRTF data sets to generate the spatialized auditory stimuli. HRTF measurement is accomplished using a variety of techniques that can require several nearly arbitrary decisions about methodology. The effects of these choices upon the resulting spatial audio interface are unclear. Sixteen participants completed a sound localization task that included real-world, broadband stimuli spatialized at eight locations on the horizontal plane. Four different HRTF data sets were utilized to spatialize the stimuli: two publicly available HRTF data sets and two data sets obtained using different in-house measurement systems. All HRTFs were obtained from the Knowles Electronics Mannequin for Acoustics Research. Unsigned localization error and proportion of front/back reversals did not differ significantly across HRTF data sets. Poorest accuracy was observed in locations near the medial (front/back) axis of the listener, mainly because of the relatively large proportions of reversals at these locations. This study suggests that the particular generalized HRTF data set chosen for spatialization is of minimal importance to the localizability of the resulting stimuli. This result will inform the design of many spatial audio interfaces that are based upon generalized HRTFs, including wayfaring devices, communication systems, and virtual reality systems.

Head related transfer function (HRTF) is a continuous function of spatial direction. In practice, only HRTFs at discrete directions can be measured. In order to obtain HRTFs at unmeasured directions, a continuous reconstruction (or interpolation) procedure is needed. In this paper, a method for continuous reconstruction of HRTF based on optimal-degree spherical harmonics expansion is developed. Expansion coefficients were derived by using the pseudo-inverse method. To address the ill-posed problem in inverse calculation, the expansion degree for each frequency bin was optimized by a heuristic method. This method searches the minimum-norm errors of the reconstructed HRTFs with respect to measured ones which were not used to derive the coefficients. The KEMAR HRTF at 710 directions and a human HRTF at 493 directions were employed in reconstruction. Measured HRTFs from KEMAR or human subject were dived into three groups according to directions, in which the first group of 2/5, the second group of 2/5, and the third group of 1/5 data were used to calculate the expansion coefficients, determine the optimal expansion degree, and evaluate the reconstruction performance, respectively. Compared with the expansion methods using a constant degree for all frequency, the reconstruction performance of the current method is prior.

It is widely acknowledged that individualized head-related transfer function (HRTF) measurements are needed to adequately capture all of the 3D spatial hearing cues. However, many perceptual studies have shown that localization accuracy in the lateral dimension is only minimally decreased by the use of non-individualized head-related transfer functions. This evidence supports the idea that the individualized components of an HRTF could be isolated from those that are more general in nature. In the present study we decomposed the HRTF at each location into average, lateral and intraconic spectral components, along with an ITD in an effort to isolate the sound localization cues that are responsible for the inter-individual differences in localization performance. HRTFs for a given listener were then reconstructed systematically with components that were both individualized and non-individualized in nature, and the effect of each modification was analyzed via a virtual localization test where brief 250 ms noise bursts were rendered with the modified HRTFs. Results indicate that the cues important for individualization of HRTFs are contained almost exclusively in the intraconic portion of the HRTF spectra and localization is only minimally affected by introducing non-individualized cues into the other HRTF components. These results provide new insights into what specific inter-individual differences in head-related acoustical features are most relevant to sound localization, and provide a framework for how future human-machine interfaces might be more effectively generalized and/or individualized.

Extensive head-related transfer function (HRTF) measurements show high HRTF repeatability, consequences of different measurement methods, and conditions covering the whole three-dimensional space [Riederer, J. Audio Eng. Soc. (Abstracts) 46, 1036 (1998), preprint 4846]. This study concentrates on specific effects on HRTFs carefully re-measured on the same Cortex dummy head applying Sennheiser KE4-211-2 microphones at its silicone putty blocked ear-canal entrances, employing 252 sound incidents including seven elevations. The effects of five different wigs (synthetic, natural, thick, thin, long and short hair) with varied hairstyles, four hats (cap, bicycle helmet, mens and womens trilby), clothes (alpaca pullover, bicycling drymax-jacket) and spectacles were investigated under 28 combinations. The influences are highly dependent on direction, frequency, and case. Clothes and eye-glasses affect minimally HRTF; hair has a stronger effect, depending on the actual hairdo (typically above 7 kHz). Hats alter intensively HRTFs (typically above 5 kHz), depending on the model. The measurements give deeper insight to the development of idiosyncratic features in binaural localization cues. The second part of the study addresses their perceptual effects [Riederer, J. Acoust. Soc. Am., this issue]. [Work supported by Graduate School of Electronics, Telecommunication and Automation; thanks to Finnish Broadcasting Company, Mr. Hellstrom; Mrs. Chen.]

The use of audio systems that employ binaural synthesis with head tracking has become increasingly popular, particularly in virtual reality gaming systems. The binaural synthesis process uses the Head-Related Transfer Functions (HRTF) as an input required to assign the directions of arrival to sounds coming from virtual sound sources in the created virtual environments. Generic HRTFs are often used for this purpose to accommodate all potential listeners. The hypothesis of the research is that the use of individual HRTF in binaural synthesis instead of generic HRTF leads to improved accuracy and quality of virtual sound source localization, thus enhancing the user experience. A novel methodology is proposed that involves the use of dynamic virtual sound sources. In the experiments, the test participants were asked to determine the direction of a dynamic virtual sound source in both the horizontal and vertical planes using both generic and individual HRTFs. The gathered data are statistically analyzed, and the accuracy of localization is assessed with respect to the type of HRTF used. The individual HRTFs of the test participants are measured using a novel and efficient method that is accessible to a broad range of users.

Listener’s own head-related transfer functions (HRTFs) are necessary for accurate sound image reproduction. The HRTFs of other listeners often cause the front-back confusion and the errors in elevation perception. It is, however, impractical to measure the HRTFs of any listener for any sound source direction because the measurement requires special apparatus and much time. On the other hand, the estimation of the entire spectrum information of listener’s own HRTF still remains as an unsolved difficult issue. One of the authors has shown that the simplified HRTFs, which is recomposed only of the first spectral peak around 4 kHz (P1) and the lowest two spectral notches (N1 and N2) above P1, extracted from the listener’s measured HRTFs in the median plane, provide almost the same localization accuracy as the measured HRTFs. While the frequency of P1 is almost constant independent of the sound source elevation and the listener, those of N1 and N2 are highly dependent on both the elevation and the listener. The present study proposes a method, which estimates the frequencies of N1 and N2 in the median plane for the individual listener from the anthropometry of the listener's pinna, and examines the validity of the method.

A high voltage damped oscillating wave generator with variable frequency has been developed using power devices (IGBT), photo devices, a designed noncore transformer and a function-generator in order to diagnose insulating materials as power apparatus (transformer, cable), enameled wires, printed circuit board (PCB), wire-harness in automobiles. The generated maximum voltage (2.5 kV) and the frequency dependency (0.01-2 kHz) were confirmed in output tests.

Head-Related Transfer Function (HRTF) measurement and extraction are important tasks for personalized-spatial audio. Many laboratories have their own apparatuses for data-collection but few studies have compared their results to a common subject or have modeled inter-dataset variances. We present a Bayesian fusion method based on Gaussian process (GP) modeling of joint spatial-frequency HRTFs over different spherical-measurement grids. Neumann KU-100 dummy HRTFs from 7 labs in the "Club Fritz" study are compared and fused to each other based on learning a set of transformations from the GP data-likelihood and covariance assumptions; parameter and hyperparameter training is automatic. Experimental results show that fused models for horizontal and median-plane HRTFs generalize the datasets better than pre-transformed ones.

Personal Alert Safety System (PASS) devices are used in the fire service to locate trapped or injured personnel. When a firefighter becomes incapacitated, the device emits an audible alarm to help rescue teams locate the downed firefighter. These devices have been mostly successful but there are still cases in which PASS is not effective, and the present project seeks to provide science-based guidance for improvements to PASS. One part of this complex problem is the effect of the protective equipment (helmet, eye protection, hood, coat) that is worn by firefighters on hearing. Since this has not previously been studied, it has not been accounted for in the current design of the PASS signal. To address this deficiency, head related transfer function (HRTF) measurements have been taken with a KEMAR acoustic mannequin wearing various combinations of the aforementioned equipment. Results indicate a reduced received level at the ear when the full complement of gear is worn, as might be expected, potentially causing a reduced detection range. In addition, the helmet and eye protection devices cause significant disruption of the normal HRTF patterns, which could potentially interfere with localization. [Work supported by U.S. Department of Homeland Security Assistance to Firefighters Grants Program.]

Distance rendering and perception of nearby virtual sound sources with a near-field filter model

The benefit of using individual head-related transfer functions (HRTFs) in binaural audio is well documented with regards to improving localization precision. However, with the increased use of binaural audio in more complex scene renderings, cognitive studies, and virtual and augmented reality simulations, the perceptual impact of HRTF selection may go beyond simple localization. In this study, the authors develop a list of attributes which qualify the perceived differences between HRTFs, providing a qualitative understanding of the perceptual variance of non-individual binaural renderings. The list of attributes was designed using a Consensus Vocabulary Protocol elicitation method. Participants followed an Individual Vocabulary Protocol elicitation procedure, describing the perceived differences between binaural stimuli based on binauralized extracts of multichannel productions. This was followed by an automated lexical reduction and a series of consensus group meetings during which participants agreed on a list of relevant attributes. Finally, the proposed list of attributes was then evaluated through a listening test, leading to eight valid perceptual attributes for describing the perceptual dimensions affected by HRTF set variations.

Personalised binaural audio requires individual head-related transfer functions (HRTFs). Nowadays, it is feasible to compute HRTFs numerically from meshes of a listener’s anatomy. These meshes require geometric details of the pinna which are difficult to capture and often corrupted by noise and outliers. The alignment of a highresolution template geometry to the captured listener geometry seems to be a promising approach to deal with these corruptions. However, such an alignment represents a multi-dimensional optimisation problem. To tackle this, we describe a parametric pinna model which reduces the representation of a non-pathological human pinna geometry from a few thousand points in space to 144 parameter dimensions. The model was evaluated in the geometric and psychoacoustic domains in terms of the Hausdorff distance distribution and simulated localisation errors, respectively. When aligned with individual ground-truth meshes, the parametric pinna model was able to represent these meshes with a small geometric error. The predicted sound-localisation performance, using the aligned meshes as a basis for HRTF calculations, was similar to that of the corresponding listener. These results indicate that the proposed parametric pinna model represents a versatile tool to create human pinna meshes with a detailed geometry for the calculation of individual HRTFs.

High performance audio and video codecs and ever increasing bandwidths of data communications networks have enabled multi-platform delivery of high definition media content via transmission channels such as terrestrial broadcast, broadband IP networks and mobile telecommunications systems. Media content consumption becomes ubiquitous and more personalized than ever before and audio is often rendered through headphones. Attentions should be paid to sound quality, and therefore high definition virtual auditory space (VAS) is sought after as an ideal solution. Stereophonic and surround sound are still commonplace while spatial audio is in its infancy to meet the demand of 2.5/3 D high definition video. Binaural headphone rendering offers ultimate spatial audio and source localization; however, individual head-related transfer functions (HRTFs), head movement tracking and suitably synthesized signals are needed to achieve its full potential. Most audio recordings to date are intended and hence best for loudspeaker rendering. Good cross-feed filters can be an interim solution to improve headphone user experience. This paper proposes a universal cross-feed filter. HRTFs at specific source locations were first considered to derive the cross-feed filters. User preferred HRTF parameters were also identified with a variety of representative soundtracks. The transfer functions were measured and simplified to derive user preferred universal cross-feed filters for all. Validation tests confirmed improved listening experience.