On the Use of a GPU-Accelerated Mobile Device Processor for Sound Source Localization

https://doi.org/10.1016/j.procs.2017.05.037Get rights and content
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Abstract

The growing interest to incorporate new features into mobile devices has increased the number of signal processing applications running over processors designed for mobile computing. A challenging signal processing field is acoustic source localization, which is attractive for applications such as automatic camera steering systems, human-machine interfaces, video gaming or audio surveillance. In this context, the emergence of systems-on-chip (SoC) that contain a small graphics accelerator (or GPU), contributes a notable increment of the computational capacity while partially retaining the appealing low-power consumption of embedded systems. This is the case, for example, of the Samsung Exynos 5422 SoC that includes a Mali-T628 MP6 GPU. This work evaluates an OpenCL-based implementation of a method for sound source localization, namely, the Steered-Response Power with Phase Transform (SRP-PHAT) algorithm, on GPUs of this type. The results show that the proposed implementation, given the audio samples, is able to perform audio localization in real time with high-resolution spatial grids using up to 12 microphones.

Keywords

Embedded systems
Sound source localization
Audio processing
Microphone arrays

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