Associate professor Rochester Institute of Technology Rochester, New York, United States
We have been investigating how to train listeners for auditory localization using an interactive augmented reality (AR) training program using generalized HRTF data. Our previous study showed that four weeks of two training sessions per week allowed listeners to improve localization performance around 7.6ยบ. In this study, we investigated the influence of specific generalized HRTF data on the individual training performance. The post-training results showed that training was more effective with one specific HRTF set. In particular, this HRTF set led to better performance in two following aspects: (1) its higher scores in the pre-training test, and (2) its consistency over the entire training period.
Authors: Sungyoung Kim (Rochester Institute of Technology), Song Hui Chon (Belmont University), Hiraku Okumura (Yamaha Corporation) and Shuichi Sakamoto (Tohoku University)
