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IEEE VR2022顶会

Empirical Evaluation of Calibration and Long-term Carryover Effects of Reverberation on Egocentric Auditory Depth Perception in VR

Wan-Yi Lin, Ying-Chu Wang, Dai-Rong Wu, Rohith Venkatakrishnan, Roshan Venkatakrishnan, Elham Ebrahimi, Christopher Pagano, Sabarish V. Babu, Wen-Chieh Lin

2022年份
11被引次数

摘要

Distance compression, which refers to the underestimation of ego-centric distance to objects, is a common problem in immersive virtual environments. Besides visually compensating the compressed distance, several studies have shown that auditory information can be an alternative solution for this problem. In particular, reverberation time (RT) has been proven to be an effective method to compensate distance compression. To further explore the feasibility of applying audio information to improve distance perception, we investigate whether users’ egocentric distance perception can be calibrated, and whether the calibrated effect can be carried over and even sustain for a longer duration. We conducted a study to understand the perceptual learning and carryover effects by using RT as stimuli for users to perceive distance in IVEs. The results show that the carryover effect exists after calibration, which indicates people can learn to perceive distances by attuning reverberation time, and the accuracy even remains a constant level after 6 months. Our findings could potentially be utilized to improve the distance perception in VR systems as the calibration of auditory distance perception in VR could sustain for several months. This could eventually avoid the burden of frequent training regimens.

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