Last Saturday, Riccardo presented the paper “A hybrid approach to structural modeling of individualized HRTFs” (R. Miccini, S. Spagnol) at the IEEE 6th VR Workshop on Sonic Interactions in Virtual Environments, as part of the 28th IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR 2021). Like last year the conference has been an entirely virtual event, and the workshop was live-streamed for free. About 80 participants attended the workshop. You can watch the recorded presentation here (starting at 01:58:43) and download the final version of the paper here.
The paper presents a hybrid approach to individualized head-related transfer function (HRTF) modeling which requires only 3 anthropometric measurements and an image of the pinna. A prediction algorithm based on variational autoencoders synthesizes a pinna-related response from the image, which is used to filter a measured head-and-torso response. The interaural time difference is then manipulated to match that of the HUTUBS dataset subject minimizing the predicted localization error. The results are evaluated using spectral distortion and an auditory localization model. While the latter is inconclusive regarding the efficacy of the structural model, the former metric shows promising results with encoding HRTFs.