An Efficient Implementation of Parallel Parametric HRTF Models for Binaural Sound Synthesis in Mobile Multimedia
The extended use of mobile multimedia devices in applications like gaming, 3D video and audio reproduction, immersive teleconferencing, or virtual and augmented reality, is demanding efficient algorithms and methodologies. All these applications require real-time spatial audio engines with the capab...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9028216/ |
| _version_ | 1819276400051355648 |
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| author | Jose A. Belloch German Ramos Jose M. Badia Maximo Cobos |
| author_facet | Jose A. Belloch German Ramos Jose M. Badia Maximo Cobos |
| author_sort | Jose A. Belloch |
| collection | DOAJ |
| description | The extended use of mobile multimedia devices in applications like gaming, 3D video and audio reproduction, immersive teleconferencing, or virtual and augmented reality, is demanding efficient algorithms and methodologies. All these applications require real-time spatial audio engines with the capability of dealing with intensive signal processing operations while facing a number of constraints related to computational cost, latency and energy consumption. Most mobile multimedia devices include a Graphics Processing Unit (GPU) that is primarily used to accelerate video processing tasks, providing high computational capabilities due to its inherent parallel architecture. This paper describes a scalable parallel implementation of a real-time binaural audio engine for GPU-equipped mobile devices. The engine is based on a set of head-related transfer functions (HRTFs) modelled with a parametric parallel structure, allowing efficient synthesis and interpolation while reducing the size required for HRTF data storage. Several strategies to optimize the GPU implementation are evaluated over a well-known kind of processor present in a wide range of mobile devices. In this context, we analyze both the energy consumption and real-time capabilities of the system by exploring different GPU and CPU configuration alternatives. Moreover, the implementation has been conducted using the OpenCL framework, guarantying the portability of the code. |
| first_indexed | 2024-12-23T23:39:37Z |
| format | Article |
| id | doaj.art-60b16344b1764be493d34f42c6b47f97 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-23T23:39:37Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-60b16344b1764be493d34f42c6b47f972022-12-21T17:25:44ZengIEEEIEEE Access2169-35362020-01-018495624957310.1109/ACCESS.2020.29794899028216An Efficient Implementation of Parallel Parametric HRTF Models for Binaural Sound Synthesis in Mobile MultimediaJose A. Belloch0https://orcid.org/0000-0002-2595-1828German Ramos1Jose M. Badia2https://orcid.org/0000-0002-5927-0449Maximo Cobos3Departamento de Tecnología Electrónica, Universidad Carlos III de Madrid, Leganes, SpainiTEAM Institute, Universitat Politecnica de Valencia, Valencia, SpainDepartamento de Ingeniería y Ciencia de Computación, Universitat Jaume I de Castello, Castellon, SpainDepartamento Informàtica, Universitat de València, Valencia, SpainThe extended use of mobile multimedia devices in applications like gaming, 3D video and audio reproduction, immersive teleconferencing, or virtual and augmented reality, is demanding efficient algorithms and methodologies. All these applications require real-time spatial audio engines with the capability of dealing with intensive signal processing operations while facing a number of constraints related to computational cost, latency and energy consumption. Most mobile multimedia devices include a Graphics Processing Unit (GPU) that is primarily used to accelerate video processing tasks, providing high computational capabilities due to its inherent parallel architecture. This paper describes a scalable parallel implementation of a real-time binaural audio engine for GPU-equipped mobile devices. The engine is based on a set of head-related transfer functions (HRTFs) modelled with a parametric parallel structure, allowing efficient synthesis and interpolation while reducing the size required for HRTF data storage. Several strategies to optimize the GPU implementation are evaluated over a well-known kind of processor present in a wide range of mobile devices. In this context, we analyze both the energy consumption and real-time capabilities of the system by exploring different GPU and CPU configuration alternatives. Moreover, the implementation has been conducted using the OpenCL framework, guarantying the portability of the code.https://ieeexplore.ieee.org/document/9028216/Binaural synthesisHRTF modelingGPUparallel filtersparametric modelinterpolation |
| spellingShingle | Jose A. Belloch German Ramos Jose M. Badia Maximo Cobos An Efficient Implementation of Parallel Parametric HRTF Models for Binaural Sound Synthesis in Mobile Multimedia IEEE Access Binaural synthesis HRTF modeling GPU parallel filters parametric model interpolation |
| title | An Efficient Implementation of Parallel Parametric HRTF Models for Binaural Sound Synthesis in Mobile Multimedia |
| title_full | An Efficient Implementation of Parallel Parametric HRTF Models for Binaural Sound Synthesis in Mobile Multimedia |
| title_fullStr | An Efficient Implementation of Parallel Parametric HRTF Models for Binaural Sound Synthesis in Mobile Multimedia |
| title_full_unstemmed | An Efficient Implementation of Parallel Parametric HRTF Models for Binaural Sound Synthesis in Mobile Multimedia |
| title_short | An Efficient Implementation of Parallel Parametric HRTF Models for Binaural Sound Synthesis in Mobile Multimedia |
| title_sort | efficient implementation of parallel parametric hrtf models for binaural sound synthesis in mobile multimedia |
| topic | Binaural synthesis HRTF modeling GPU parallel filters parametric model interpolation |
| url | https://ieeexplore.ieee.org/document/9028216/ |
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