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JO. A.. Belloch, M. Ferrer, A. Gonzalez, J. Lorente, and AN. M.. Vidal, "GPU-Based WFS Systems with Mobile Virtual Sound Sources and Room Compensation," Paper P-1, (2013 September.). doi: JO. A.. Belloch, M. Ferrer, A. Gonzalez, J. Lorente, and AN. M.. Vidal, "GPU-Based WFS Systems with Mobile Virtual Sound Sources and Room Compensation," Paper P-1, (2013 September.). doi:
Abstract: Wave Field Synthesis (WFS) is a spatial audio reproduction system that provides an accurate spatial sound field in a wide area. This sound field is rendered through a high number of loudspeakers to emulate virtual sound sources. WFS systems require high computational capacity since they involve multiple loudspeakers and multiple virtual sources. Furthermore improvements of the spatial audio perception imply even higher processing capacity, mainly to avoid artifacts when the virtual sources move, and compensate the room e ects at certain control points within the listening area. Graphics Processing Units (GPUs) are well-known for their potential in highly parallel data processing. In this paper, we propose a GPU implementation that yields maximum parallelism by adapting the required computations to the di erent GPU architectures (Tesla, Fermi and Kepler).

@article{belloch2013gpu-based,
author={belloch, jose a. and ferrer, miguel and gonzalez, alberto and lorente, jorge and vidal, antonio m.},
journal={journal of the audio engineering society},
title={gpu-based wfs systems with mobile virtual sound sources and room compensation},
year={2013},
volume={},
number={},
pages={},
doi={},
month={september},} @article{belloch2013gpu-based,
author={belloch, jose a. and ferrer, miguel and gonzalez, alberto and lorente, jorge and vidal, antonio m.},
journal={journal of the audio engineering society},
title={gpu-based wfs systems with mobile virtual sound sources and room compensation},
year={2013},
volume={},
number={},
pages={},
doi={},
month={september},
abstract={wave field synthesis (wfs) is a spatial audio reproduction system that provides an accurate spatial sound field in a wide area. this sound field is rendered through a high number of loudspeakers to emulate virtual sound sources. wfs systems require high computational capacity since they involve multiple loudspeakers and multiple virtual sources. furthermore improvements of the spatial audio perception imply even higher processing capacity, mainly to avoid artifacts when the virtual sources move, and compensate the room e ects at certain control points within the listening area. graphics processing units (gpus) are well-known for their potential in highly parallel data processing. in this paper, we propose a gpu implementation that yields maximum parallelism by adapting the required computations to the di erent gpu architectures (tesla, fermi and kepler).},}

TY - paper
TI - GPU-Based WFS Systems with Mobile Virtual Sound Sources and Room Compensation
SP - EP -
AU - Belloch, Jose A.
AU - Ferrer, Miguel
AU - Gonzalez, Alberto
AU - Lorente, Jorge
AU - Vidal, Antonio M.
PY - 2013
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - September 2013 TY - paper
TI - GPU-Based WFS Systems with Mobile Virtual Sound Sources and Room Compensation
SP - EP -
AU - Belloch, Jose A.
AU - Ferrer, Miguel
AU - Gonzalez, Alberto
AU - Lorente, Jorge
AU - Vidal, Antonio M.
PY - 2013
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - September 2013
AB - Wave Field Synthesis (WFS) is a spatial audio reproduction system that provides an accurate spatial sound field in a wide area. This sound field is rendered through a high number of loudspeakers to emulate virtual sound sources. WFS systems require high computational capacity since they involve multiple loudspeakers and multiple virtual sources. Furthermore improvements of the spatial audio perception imply even higher processing capacity, mainly to avoid artifacts when the virtual sources move, and compensate the room e ects at certain control points within the listening area. Graphics Processing Units (GPUs) are well-known for their potential in highly parallel data processing. In this paper, we propose a GPU implementation that yields maximum parallelism by adapting the required computations to the di erent GPU architectures (Tesla, Fermi and Kepler).