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Energy-Efficient Approximate Speech Signal Processing for Wearable Devices

Authors
Park, TaejoonShin, KyoosikKim, 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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Shin, Kyoo sik
ERICA 공학대학 (DEPARTMENT OF ROBOT ENGINEERING)
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