Individualizing Head-Related Transfer Functions Using Smartphones

Background

Head-Related Transfer Functions (HRTFs) represent an acoustic filtering response of humans’ outer ear, head, and torso. This natural filtering system plays a key role in human binaural auditory systems that allows people to not only hear but also to perceive the direction of incoming sounds. The HRTF characterizes how a human ear receives sounds from a point in space, and depends on, for example, the shapes of a person’s head, pinna, and torso. Accurate estimations of HRTFs for human subjects are crucial in augmented or virtual realities applications, among other applications. Unfortunately, approaches for HRTF estimation generally rely on specialized devices or lengthy measurement processes. Additionally, using another person’s HRTF, or a generic HRTF, will lead to errors in acoustic spatialization and unpleasant auditory experiences.

Technology Overview

Researchers at McMaster have developed a novel lightweight process to obtain individualized HRTFs that make it possible for individuals to determine an individualized HRTF at home, without specialized/expensive equipment. The process consists of two key components: a measurement procedure that collects data from spatial locations using in-ear microphones and a smartphone, and a neural network that can be individualized to predict HRTFs of new subjects from sparse measurements. The measurement procedure is fast, lightweight, and easy to conduct. Given measurement data from as low as 60 sparse locations, the deep neural network model can be adapted to generate individualized HRTFs for all directions.

Further details:

Zandi, Navid H., et al. “Individualizing Head-Related Transfer Functions for Binaural Acoustic Applications.” ArXiv:2203.11138 [Cs, Eess], 21 Mar. 2022, arxiv.org/abs/2203.11138.

Benefits

• Cheap: no need for specialized equipment.
• Simple: no need for elaborative user anthropometric measurements.
• Fast: the total measurement time is less than 5 minutes.
• Accurate: it can produce more accurate individualized HRTFs than simulation-based methods.

Applications

• Estimation of HRTFs in virtual reality and augmented reality applications
• 3D Audio sound

Opportunity

McMaster University is seeking for technology licensing opportunities and research collaboration.