Browse > Article
http://dx.doi.org/10.4218/etrij.17.0116.0462

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)
Publication Information
ETRI Journal / v.39, no.2, 2017 , pp. 145-150 More about this Journal
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
Wearable devices; Audio signal processing; Approximate computing; Approximate multiplier; Successive approximate register ADC;
Citations & Related Records
연도 인용수 순위
  • Reference
1 R. Hegde and N.R. Shanbhag, "Energy-Efficient Signal Processing Via Algorithmic Noise-Tolerance," IEEE/ACM Int. Symp. Low Power Electron. Design, San Diego, CA, USA, Aug. 16-17, 1999, pp. 30-35.
2 S. Narayanamoorthy et al., "Energy-Efficient Approximate Multiplication for Digital Signal Processing and Classification Applications," IEEE Trans. Very Large Scale Integr. Syst., vol. 23, no. 6, June 2015, pp. 1180-1184.   DOI
3 F.M. Yaul and A.P. Chandrakasan, "A 10 b 0.6 nW SAR ADC with Data-Dependent Energy Savings Using LSB-First Successive Approximation," IEEE Int. Solid-State Circuits Conf. Digest Tech. Papers, San Francisco, CA, USA, Feb. 9-13, 2014, pp. 198-199.
4 A. Spriet et al., "Adaptive Feedback Cancellation in Hearing Aids," J. Franklin Inst., vol. 343, no. 6, Sept. 2006, pp. 545-573.   DOI
5 Open Speech Repository, American English. http://www.voiptroubleshooter.com/open_speech/american.html
6 IEEE Subcommittee on Subjective Measures, "IEEE Recommended Practice for Speech Quality Measurements," IEEE Trans. Audio Electroacoustics, vol. 17, no. 3, Sept. 1969, pp. 225-246.   DOI
7 P.J.A. Harpe et al., "A 26 W 8 bit 10 MS/s Asynchronous SAR ADC for Low Energy Radios," IEEE J. Solid-State Circuits, vol. 46, no. 7, July 2011, pp. 1585-1595.   DOI
8 Y. Hu and P.C. Loizou, "Evaluation of Objective Quality Measures for Speech Enhancement," IEEE Trans. Audio, Speech Language Process., vol. 16, no. 1, Jan. 2008, pp. 229-238.   DOI
9 Psytechnics, PESQ: an Introduction. http://www.sageinst.com/downloads/960B/wp_pesq_introduction.pdf