Energy-Efficient Approximate Speech Signal Processing for Wearable Devices
- Authors
- Park, Taejoon; Shin, Kyoosik; Kim, Nam Sung
- Issue Date
- Apr-2017
- Publisher
- WILEY
- Keywords
- Wearable devices; Audio signal processing; Approximate computing; Approximate multiplier; Successive approximate register ADC
- Citation
- ETRI JOURNAL, v.39, no.2, pp.145 - 150
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- ETRI JOURNAL
- Volume
- 39
- Number
- 2
- Start Page
- 145
- End Page
- 150
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/10055
- DOI
- 10.4218/etrij.17.0116.0462
- ISSN
- 1225-6463
- 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 similar to 40% lower energy consumption with similar to 5% higher sound quality than a traditional one that optimizes only the bit width of SSP.
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Collections - COLLEGE OF ENGINEERING SCIENCES > DEPARTMENT OF ROBOT ENGINEERING > 1. Journal Articles
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