Energy-Efficient Approximate Speech Signal Processing for Wearable Devices

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 effi...

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Bibliographic Details
Published in:ETRI journal 2017-04, Vol.39 (2), p.145-150
Main Authors: Park, Taejoon, Shin, Kyoosik, Kim, Nam Sung
Format: Article
Language:Korean
Online Access:Get full text
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Summary: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.
ISSN:1225-6463
2233-7326