  Head Related Transfer Functions (HRTFs) play a crucial role in creating
immersive spatial audio experiences. However, HRTFs differ significantly from
person to person, and traditional methods for estimating personalized HRTFs are
expensive, time-consuming, and require specialized equipment. We imagine a
world where your personalized HRTF can be determined by capturing data through
earbuds in everyday environments. In this paper, we propose a novel approach
for deriving personalized HRTFs that only relies on in-the-wild binaural
recordings and head tracking data. By analyzing how sounds change as the user
rotates their head through different environments with different noise sources,
we can accurately estimate their personalized HRTF. Our results show that our
predicted HRTFs closely match ground-truth HRTFs measured in an anechoic
chamber. Furthermore, listening studies demonstrate that our personalized HRTFs
significantly improve sound localization and reduce front-back confusion in
virtual environments. Our approach offers an efficient and accessible method
for deriving personalized HRTFs and has the potential to greatly improve
spatial audio experiences.
