A Parallel Approach to HRTF Approximation and Interpolation Based on a Parametric Filter Model
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Other documents of the author: Ramos, German; Cobos, Maximo; Bank, Balázs; BELLOCH, JOSE A.
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Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/8620
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Title
A Parallel Approach to HRTF Approximation and Interpolation Based on a Parametric Filter ModelDate
2017-10Publisher
Institute of Electrical and Electronics Engineers (IEEE)Bibliographic citation
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.Type
info:eu-repo/semantics/articlePublisher version
http://ieeexplore.ieee.org/abstract/document/8013136/Version
info:eu-repo/semantics/acceptedVersionSubject
Abstract
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 ... [+]
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. [-]
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