8161

Multi-user real-time speech recognition with a GPU

Jungsuk Kim
Department of Electrical Engineering and Computer Science, Seoul National University, 599 Gwanangno, Gwanak-gu, Seoul, 151-744, Korea
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012

@inproceedings{kim2012multi,

   title={Multi-user real-time speech recognition with a GPU},

   author={Kim, J. and Sung, W.},

   booktitle={Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on},

   pages={1617–1620},

   year={2012},

   organization={IEEE}

}

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We have developed a multi-user large vocabulary speech recognition system employing a fully composed one-level weighted finite state transducer (WFST) based network on a Graphics Processing Unit (GPU). This system improves the overall throughput and latency of speech recognition engine which processes multiple users’ utterances at the same time with efficient scheduling, parameter sharing, and communication overhead reduction techniques. We conduct both batch speech simulation and trace driven online simulation to access the performance of the developed system. Traces are generated based on a queueing model.
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