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Design and Exploration of an ARC-Coprocessor for LSTM Based Audio Applications

Authors:: Birke, S. , Hartmann, B. , Auras, D. , Wloka, M. , Ascheid, G. , Leupers, R.
Book Title:: 2022 IEEE Nordic Circuits and Systems Conference (NorCAS)
Pages:: p.p. 1-7
Date:: 2022
DOI:: 10.1109/NorCAS57515.2022.9934553
hsb:: RWTH-2022-10261
Language:: English
Abstract:: Machine Learning (ML) techniques are applied to solve automation tasks in more and more scenarios of our daily life. For instance, Keyword Spotting applications are of interest for Internet-of-things devices in a smart home or for human-machine interaction. Different ML techniques, such as Neural Networks including Long-Short Term Memories, recently achieve reasonable accuracy above 95 % [1]. Therefore, we propose an accelerator for the Keyword spotter as a specialized coprocessor in order to retain the flexibility to fit different network structures, while the energy efficiency is increased.
Download:: BibTeX