14.8 KASP: A 96.8% 10-Keyword Accuracy and 1.68μJ/Classification Keyword Spotting and Speaker Verification Processor Using Adaptive Beamforming and Progressive Wake-Up-Reference-Cited by-同舟云学术

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14.8 KASP: A 96.8% 10-Keyword Accuracy and 1.68μJ/Classification Keyword Spotting and Speaker Verification Processor Using Adaptive Beamforming and Progressive Wake-Up

Published:2024-02-18 Issue: Volume: Page:268-270
ISSN:
Container-title:2024 IEEE International Solid-State Circuits Conference (ISSCC)
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Author:

Xiao Jianbiao¹,Zhang Xuhui¹,Zhu Shijian¹,Yang Zhengwei¹,Du Meng¹,Ji Chunsheng¹,Long Yu¹,Chen Xiao²,Miao Xiaoyu²,Zhou Liang¹,Chang Liang¹,Liu Shanshan¹,Zhou Jun¹

Affiliation:

1. University of Electronic Science and Technology of China,Chengdu,China

2. China Micro Semicon,Chengdu,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10454133/10454267/10454492.pdf?arnumber=10454492

Reference9 articles.

1. An Eight-Element Frequency-Selective Acoustic Beamformer and Bitstream Feature Extractor

2. A Multimode 157μW 4-Channel 80dBA-SNDR Speech-Recognition Frontend With Self-DOA Correction Adaptive Beamformer

3. Localization-Driven Speech Enhancement in Noisy Multi-Speaker Hospital Environments Using Deep Learning and Meta Learning

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

5. A Target-Separable BWN Inspired Speech Recognition Processor with Low-power Precision-adaptive Approximate Computing

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