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Energy-Efficient Approximate Speech Signal Processing for Wearable Devices

  • Park, Taejoon (Department of Robotics Engineering, Hanyang University) ;
  • Shin, Kyoosik (Department of Robotics Engineering, Hanyang University) ;
  • Kim, Nam Sung (Department of Electrical and Computer Engineering, University of Illinois)
  • Received : 2016.07.05
  • Accepted : 2017.01.12
  • Published : 2017.04.01

Abstract

As wearable devices are powered by batteries, they need to consume as little energy as possible. To address this challenge, in this article, we propose a synergistic technique for energy-efficient approximate speech signal processing (ASSP) for wearable devices. More specifically, to enable the efficient trade-off between energy consumption and sound quality, we synergistically integrate an approximate multiplier and a successive approximate register analog-to-digital converter using our enhanced conversion algorithm. The proposed ASSP technique provides ~40% lower energy consumption with ~5% higher sound quality than a traditional one that optimizes only the bit width of SSP.

Keywords

References

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