Morphological Weighting Improves Individualized Prediction of HRTF Directivity Patterns

In this work, we explore the potential for morphological weighting of different regions of the pinna (outer ear) to improve the prediction of acoustic directivity patterns associated with head-related transfer functions. Using a large deformation diffeomorphic metric mapping framework, we apply kernel principal component analysis to model the pinna morphology. Different regions of the pinna can be weighted differently prior to the kernel principal component analysis. By varying the weights applied to the various regions of the pinna, we begin to learn the relative importance of the various regions to the acoustic directivity of the ear as a function of frequency. The pinna is divided into nine parts comprising the helix, scaphoid fossa, triangular fossa, concha rim, cymba concha, cavum concha, conchal ridge, ear lobe, and back of the ear. Results indicate that weighting the conchal region (concha rim, cavum and cymba concha) improves the predicted acoustic directivity for frequency bands centered around 3 kHz, 7 kHz, 10 kHz and 13 kHz. Similarly, weighting the triangular and scaphoid fossa improves the prediction of acoustic directivity in frequency bands centered around 7 kHz, 13 kHz and 15.5 kHz.