2024-03-29T05:19:37Zhttps://repositori.uji.es/oai/requestoai:repositori.uji.es:10234/1700562020-02-06T14:51:04Zcom_10234_7036com_10234_9col_10234_8620
00925njm 22002777a 4500
dc
Ramos, German
author
Cobos, Maximo
author
Bank, Balázs
author
BELLOCH, JOSE A.
author
2017-10
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.
RAMOS, German, et al. A Parallel Approach to HRTF Approximation and Interpolation Based on a Parametric Filter Model. IEEE Signal Processing Letters, 2017, vol. 24, no 10, p. 1507-1511.
http://hdl.handle.net/10234/170056
http://dx.doi.org/10.1109/LSP.2017.2741724
binaural synthesis
graphic processing unit (GPU)
head-related transfer function (HRTF) modeling
interpolation
parallel filters
A Parallel Approach to HRTF Approximation and Interpolation Based on a Parametric Filter Model