2015
DOI: 10.1016/j.eswa.2015.02.056
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Abstract: ElsevierBelloch Rodríguez, JA.; Vidal Maciá, AM.; Cobos Serrano, M. (2015). On the performance of multi-GPU-based expert systems for acoustic localization involving massive microphone array. Expert Systems with Applications. 42 (13) AbstractSound source localization is an important topic in expert systems involving microphone arrays, such as automatic camera steering systems, human-machine interaction, video gaming or audio surveillance. The Steered Response Power with Phase Transform (SRP-PHAT) algorithm is… Show more

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Cited by 26 publications
(17 citation statements)
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“…At runtime, the scheduler distributes the thread blocks among Streaming Multiprocessors (SMs). Therefore, most of the GPU-based research works in different fields, such as [41], [42], using a priori analysis of thread blocks and grids sizes to optimize computational efficiency. Other important issues to take into account are the occupancy of the GPU, the efficient use of the fastest memory levels of the GPU, and the granularity of the computations on every thread [43,Chap.…”
Section: B Objectives Using Gpumentioning
confidence: 99%
“…At runtime, the scheduler distributes the thread blocks among Streaming Multiprocessors (SMs). Therefore, most of the GPU-based research works in different fields, such as [41], [42], using a priori analysis of thread blocks and grids sizes to optimize computational efficiency. Other important issues to take into account are the occupancy of the GPU, the efficient use of the fastest memory levels of the GPU, and the granularity of the computations on every thread [43,Chap.…”
Section: B Objectives Using Gpumentioning
confidence: 99%
“…In particular, classical VADs are piloted by the analysis of specific signal characteristics (Benyassine, Shlomot, Su, Massaloux, Lamblin & Petit, 1997;Yantorno, Krishnamachari, Lovekin, Benincasa & Wenndt, 2001) or rely on statistical models of the speech and noise signals (Sohn, Kim & Sung, 1999;Lee, Nakamura, Nisimura, Saruwatari & Shikano, 2004). Similarly, the more general sound localization task has been tackled by classical techniques such as Cross Spectrum Phase (CSP) (Knapp & Carter, 1976) and Steered-Response Power Phase Transform (SRP-PHAT) (Do, Silverman & Yu, 2007;Seewald, Gonzaga Jr, Veronez, Minotto & Jung, 2014;Belloch, Gonzalez, Vidal & Cobos, 2015). These techniques rely on two main stages: initially cross-correlation is employed for estimating the Time Difference of Arrival (TDOA) between each microphone pair under study, then TDOAs are combined and jointly processed for localizing the sound source.…”
Section: Introductionmentioning
confidence: 99%
“…In this context, the use of graphics processing units (GPUs) for implementing SRP-based approaches is specially promising [96,97]. In [98] the performance of SRP-PHAT is analyzed over a massive multichannel processing framework in a multi-GPU system, analyzing its performance as a function of the number of microphones and available computational resources in the system. Note, however, that the performance of SRP approaches is also related to the properties of the sound sources, such as their bandwidth or their low-pass/pass-band nature [99,100].…”
Section: Modified Srp-phat (M-srp)mentioning
confidence: 99%