Head-Related Transfer Functions for Dynamic Listeners in Virtual Reality

Rummukainen, Olli; Robotham, Thomas; Habets, Emanuël A. P.

doi:10.3390/app11146646

Cited by 8 publications

(4 citation statements)

References 37 publications

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“…Many datasets of HRTFs are already available, and several methods have been developed for measuring personal HRTFs in an easy way [ 5 , 6 ]. Various studies show the advantage of using one’s own measured HRTFs in binaural systems [ 7 , 8 ], rather than relying on generic ones.…”

Section: Introductionmentioning

confidence: 99%

The Performance of Inertial Measurement Unit Sensors on Various Hardware Platforms for Binaural Head-Tracking Applications

Franček

Jambrošić²,

Horvat³

et al. 2023

Sensors

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Binaural synthesis with head tracking is often used in spatial audio systems. The devices used for head tracking must provide data on the orientation of the listener’s head. These data need to be highly accurate, and they need to be provided as fast and as frequently as possible. Therefore, head-tracking devices need to be equipped with high-quality inertial measurement unit (IMU) sensors. Since IMUs readily include triaxial accelerometers, gyroscopes, and magnetometers, it is crucial that all of these sensors perform well, as the head orientation is calculated from all sensor outputs. This paper discusses the challenges encountered in the process of the performance assessment of IMUs through appropriate measurements. Three distinct hardware platforms were investigated: five IMU sensors either connected to Arduino-based embedded systems or being an integral part of one, five smartphones across a broad range of overall quality with integrated IMUs, and a commercial virtual reality unit that utilizes a headset with integrated IMUs. An innovative measurement method is presented and proposed for comparing the performance of sensors on all three platforms. The results of the measurements performed using the proposed method show that all three investigated platforms are adequate for the acquisition of the data required for calculating the orientation of a device as the input to the binaural synthesis process. Some limitations that have been observed during the measurements, regarding data acquisition and transfer, are discussed.

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Section: Introductionmentioning

confidence: 99%

The Performance of Inertial Measurement Unit Sensors on Various Hardware Platforms for Binaural Head-Tracking Applications

Franček

Jambrošić²,

Horvat³

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…One study, in particular, confirms improvements in sound source localization by using individual HRTF over generic, but the emphasis is put on the compelling performance of a generic HRTF set [38]. On the other hand, one study found no difference between using individual HRTF and generic HRTF in dynamic virtual environments [39], although their methodology and experimental design are considerably different from the ones presented in this research. The implications of these contradictory findings suggest that additional investigation might help to identify the most informative dynamic cues in order to enhance our comprehension of the variations between the experimental conditions, which may clarify the underlying factors contributing to the observed discrepancies.…”

Section: Discussionmentioning

confidence: 48%

The Accuracy of Dynamic Sound Source Localization and Recognition Ability of Individual Head-Related Transfer Functions in Binaural Audio Systems with Head Tracking

et al. 2023

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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.

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“…In a study involving users of VR technology, researchers compared personalized HRTFs to generic ones [ 8 ]. The study found that, during a static localization test, there was no statistically significant difference in accuracy between personalized and generic HRTFs.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Training on Localizing HoloLens-Generated 3D Sound Sources

Ryu,

Lee,

Park

2024

Sensors

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Sound localization is a crucial aspect of human auditory perception. VR (virtual reality) technologies provide immersive audio platforms that allow human listeners to experience natural sounds based on their ability to localize sound. However, the simulations of sound generated by these platforms, which are based on the general head-related transfer function (HRTF), often lack accuracy in terms of individual sound perception and localization due to significant individual differences in this function. In this study, we aimed to investigate the disparities between the perceived locations of sound sources by users and the locations generated by the platform. Our goal was to determine if it is possible to train users to adapt to the platform-generated sound sources. We utilized the Microsoft HoloLens 2 virtual platform and collected data from 12 subjects based on six separate training sessions arranged in 2 weeks. We employed three modes of training to assess their effects on sound localization, in particular for studying the impacts of multimodal error, visual, and sound guidance in combination with kinesthetic/postural guidance, on the effectiveness of the training. We analyzed the collected data in terms of the training effect between pre- and post-sessions as well as the retention effect between two separate sessions based on subject-wise paired statistics. Our findings indicate that, as far as the training effect between pre- and post-sessions is concerned, the effect is proven to be statistically significant, in particular in the case wherein kinesthetic/postural guidance is mixed with visual and sound guidance. Conversely, visual error guidance alone was found to be largely ineffective. On the other hand, as far as the retention effect between two separate sessions is concerned, we could not find any meaningful statistical implication on the effect for all three error guidance modes out of the 2-week session of training. These findings can contribute to the improvement of VR technologies by ensuring they are designed to optimize human sound localization abilities.

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Head-Related Transfer Functions for Dynamic Listeners in Virtual Reality

Cited by 8 publications

References 37 publications

The Performance of Inertial Measurement Unit Sensors on Various Hardware Platforms for Binaural Head-Tracking Applications

The Performance of Inertial Measurement Unit Sensors on Various Hardware Platforms for Binaural Head-Tracking Applications

The Accuracy of Dynamic Sound Source Localization and Recognition Ability of Individual Head-Related Transfer Functions in Binaural Audio Systems with Head Tracking

The Effect of Training on Localizing HoloLens-Generated 3D Sound Sources

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