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Headphone-Based Virtual Spatialization of Sound with a GPU Accelerator

This paper describes the design of a binaural headphone-based multisource spatial-audio application using a Graphical Processing Unit (GPU) as the compute engine. It is a highly parallel programmable coprocessor that provides massive computation power when the algorithm is properly parallelized. To render a sound source at a specific location, audio samples must be convolved with Head Related Impulse Responses (HRIR) filters for that location. A data base of HRIR at fixed spatial positions is used. Solutions have been developed to handle two problems: synthesizing sound sources positions that are not in the HRIR database, and virtualizing the movement of the sound sources between different positions. The GPU is particularly appropriate for simultaneously executing multiple convolutions without overloading the main CPU. The results show that the proposed application is able to handle up to 240 sources simultaneously when all sources are moving.

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JAES Volume 61 Issue 7/8 pp. 546-561; July 2013
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