A Parallel Approach to HRTF Approximation and Interpolation Based on a Parametric Filter Model

"© 2017 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."[EN] Spatial audio-rendering techniques using head-related transfer functions (HRTFs) are currently used in many different contexts such as immersive teleconferencing systems, gaming, or 3-D audio reproduction. Since all these applications usually involve real-time constraints, efficient processing structures for HRTF modeling and interpolation are necessary for providing real-time binaural audio solutions. This letter presents a parametric parallel model that allows us to perform HRTF filtering and interpolation efficiently from an input HRTF dataset. The resulting model, which is an adaptation from a recently proposed modeling technique, not only reduces the size of HRTF datasets significantly, but also allows for simplified interpolation and real-time computation over parallel processors. In order to discuss the suitability of this new model, an implementation over a graphic processing unit is presented.This work was supported by the Spanish Ministry of Economy and Competitiveness under Grant TEC2012-37945-C02-02 and FEDER funds and by the UNKP-16-4-III New National Excellence Program of the Hungarian Ministry of Human Capacities. The work of J. A. Belloch was supported by GVA Postdoctoral Contract APOSTD/2016/069.Ramos Peinado, G.; Cobos Serrano, M.; Bank, B.; Belloch Rodríguez, JA. (2017). A Parallel Approach to HRTF Approximation and Interpolation Based on a Parametric Filter Model. IEEE Signal Processing Letters. 24(10):1507-1511. https://doi.org/10.1109/LSP.2017.274172415071511241