A TWN Inspired Speaker Verification Processor with Hardware-friendly Weight Quantization-Reference-Cited by-同舟云学术

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A TWN Inspired Speaker Verification Processor with Hardware-friendly Weight Quantization

Published:2022-10-28 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA)
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Author:

Zhang Xuanhao¹,Wu Haige¹,Zhang Renyuan²,Xu Zihang³,Zhang Hao⁴,Liu Bo¹,Cai Hao¹

Affiliation:

1. School of Electronic Science and Engineering, Southeast University,Nanjing,China

2. School of Integrated Circuits, Southeast University,Wuxi,China

3. Chien-Shiung Wu College, Southeast University,Nanjing,China

4. Nanjing Research Institute of Electronics Technology,Nanjing,China

Funder

National Key R&D Program of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9962812/9962965/09963121.pdf?arnumber=9963121

Reference4 articles.

1. A 141 UW, 2.46 PJ/Neuron Binarized Convolutional Neural Network Based Self-Learning Speech Recognition Processor in 28NM CMOS

2. Vocell: A 65-nm Speech-Triggered Wake-Up SoC for 10-$\mu$ W Keyword Spotting and Speaker Verification

3. VLSI Design for SVM-Based Speaker Verification System

4. A 3.77TOPS/W Convolutional Neural Network Processor With Priority-Driven Kernel Optimization

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