Energy-efficient approximate speech signal processing for wearable devices

Taejoon Park, Kyoosik Shin, Nam Sung Kim

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)145-150
Number of pages6
JournalETRI Journal
Volume39
Issue number2
DOIs
StatePublished - Apr 1 2017

Keywords

  • Approximate computing
  • Approximate multiplier
  • Audio signal processing
  • Successive approximate register ADC
  • Wearable devices

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Computer Science(all)
  • Electrical and Electronic Engineering

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