Abstract:

The emergence of commercial virtual reality devices has reinvigorated the need for research in realistic audio for virtual environments. Realistic virtual audio is often realized through the use of head-related transfer functions (HRTFs) that are costly to measure and individualistic to each listener, thus making their use unscalable. Subjective selection allows a listener to pick their own HRTF from a database of premeasured HRTFs. While this is a more scalable option further research is needed to examine listeners’ consistency in choosing their own HRTFs. The present study extends the current subjective selection research by quantifying the reliability of subjectively selected HRTFs by 12 participants over time in a non-eliminating perceptual discrimination task.