LATTE: Low-power Audio Transform with TrueNorth Ecosystem

Wei Yu Tsai, Davis R. Barch, Andrew S. Cassidy, Michael V. DeBole, Alexander Andreopoulos, Bryan L. Jackson, Myron D. Flickner, Dharmendra S. Modha, Jack Sampson, Vijaykrishnan Narayanan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

With recent advances in silicon technology, previously intractable Deep Neural Network (DNN) solutions to complex visual, auditory, and other sensory perception problems are now practical for real-time, energy constrained systems. One such advancement is IBM's TrueNorth neurosynaptic processor, containing 1 million neurons and 256 million synapses, consuming 65mW of power, and capable of operating in real-time for a variety of applications. In this work, we explore how auditory features can be extracted on the TrueNorth processor using low numerical precision while maintaining algorithmic fidelity for DNN based spoken digit recognition on isolated words from the TIDIGITS dataset. Further, we show that our Low-power Audio Transform with TrueNorth Ecosystem (LATTE) is capable of achieving a 24× reduction in energy for feature extraction over a baseline FPGA implementation using standard MFCC audio features, while only incurring a 3-6% accuracy penalty.

Original languageEnglish (US)
Title of host publication2016 International Joint Conference on Neural Networks, IJCNN 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4270-4277
Number of pages8
ISBN (Electronic)9781509006199
DOIs
StatePublished - Oct 31 2016
Event2016 International Joint Conference on Neural Networks, IJCNN 2016 - Vancouver, Canada
Duration: Jul 24 2016Jul 29 2016

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2016-October

Other

Other2016 International Joint Conference on Neural Networks, IJCNN 2016
CountryCanada
CityVancouver
Period7/24/167/29/16

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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  • Cite this

    Tsai, W. Y., Barch, D. R., Cassidy, A. S., DeBole, M. V., Andreopoulos, A., Jackson, B. L., Flickner, M. D., Modha, D. S., Sampson, J., & Narayanan, V. (2016). LATTE: Low-power Audio Transform with TrueNorth Ecosystem. In 2016 International Joint Conference on Neural Networks, IJCNN 2016 (pp. 4270-4277). [7727757] (Proceedings of the International Joint Conference on Neural Networks; Vol. 2016-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2016.7727757