IEEE - Institute of Electrical and Electronics Engineers, Inc. - A 141 UW, 2.46 PJ/Neuron Binarized Convolutional Neural Network Based Self-Learning Speech Recognition Processor in 28NM CMOS

2018 IEEE Symposium on VLSI Circuits

Author(s): Shouyi Yin ; Peng Ouyang ; Shixuan Zheng ; Dandan Song ; Xiudong Li ; Leibo Liu ; Shaojun Wei
Publisher: IEEE - Institute of Electrical and Electronics Engineers, Inc.
Publication Date: 1 June 2018
Conference Location: Honolulu, HI, USA
Conference Date: 18 June 2018
Page(s): 139 - 140
ISBN (Electronic): 978-1-5386-4214-6
DOI: 10.1109/VLSIC.2018.8502309
Regular:

An ultra-low power speech recognition processor is implemented in 28 nm CMOS technology, which is based on an optimized binary convolutional neural network (BCNN). A tailored self-learning... View More

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