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Fast acoustic computations using graphics processors

Paul R. Dixon, Tasuku Oonishi, Sadaoki Furui
Department of Computer Science, Tokyo Institute of Technology, 2-12-1, Ookayama, Meguro-ku, Tokyo, Japan, 152-8552
IEEE International Conference on Acoustics, Speech and Signal Processing, 2009. ICASSP 2009

@conference{dixon2009fast,

   title={Fast acoustic computations using graphics processors},

   author={Dixon, PR and Oonishi, T. and Furui, S.},

   booktitle={Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on},

   pages={4321–4324},

   issn={1520-6149},

   year={2009},

   organization={IEEE}

}

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In this paper we present a fast method for computing acoustic likelihoods that makes use of a graphics processing unit (GPU). After enabling the GPU acceleration the main processor runtime dedicated to acoustic scoring tasks is reduced from the largest consumer to just a few percent even when using mixture models with a large number of Gaussian components. The results show a large reduction in decoding time with no change in accuracy and we also show by using a 16bit half precision floating point format for the acoustic model parameters, storage requirements can be halved with no reduction in accuracy.
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