Corpus ID: 221585948

Hardware Aware Training for Efficient Keyword Spotting on General Purpose and Specialized Hardware

@article{Blouw2020HardwareAT,
  title={Hardware Aware Training for Efficient Keyword Spotting on General Purpose and Specialized Hardware},
  author={Peter Blouw and G. Malik and Benjamin Morcos and Aaron R. Voelker and C. Eliasmith},
  journal={ArXiv},
  year={2020},
  volume={abs/2009.04465}
}

Peter Blouw, G. Malik, +2 authors C. Eliasmith

Published 2020

Computer Science, Engineering, Mathematics

ArXiv

Keyword spotting (KWS) provides a critical user interface for many mobile and edge applications, including phones, wearables, and cars. As KWS systems are typically 'always on', maximizing both accuracy and power efficiency are central to their utility. In this work we use hardware aware training (HAT) to build new KWS neural networks based on the Legendre Memory Unit (LMU) that achieve state-of-the-art (SotA) accuracy and low parameter counts. This allows the neural network to run efficiently… CONTINUE READING

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