A 23-μW Keyword Spotting IC With Ring-Oscillator-Based Time-Domain Feature Extraction

Autor:	Kwantae Kim, Chang Gao, Rui Graca, Ilya Kiselev, Hoi-Jun Yoo, Tobi Delbruck, Shih-Chii Liu
Rok vydání:	2022
Předmět:	Electrical and Electronic Engineering Computer Science - Hardware Architecture Computer Science - Sound Electrical Engineering and Systems Science - Audio and Speech Processing
Zdroj:	IEEE Journal of Solid-State Circuits. 57:3298-3311
ISSN:	1558-173X 0018-9200
DOI:	10.1109/jssc.2022.3195610
Popis:	This article presents the first keyword spotting (KWS) IC which uses a ring-oscillator-based time-domain processing technique for its analog feature extractor (FEx). Its extensive usage of time-encoding schemes allows the analog audio signal to be processed in a fully time-domain manner except for the voltage-to-time conversion stage of the analog front-end. Benefiting from fundamental building blocks based on digital logic gates, it offers a better technology scalability compared to conventional voltage-domain designs. Fabricated in a 65 nm CMOS process, the prototyped KWS IC occupies 2.03mm$^{2}$ and dissipates 23 $\mu$W power consumption including analog FEx and digital neural network classifier. The 16-channel time-domain FEx achieves 54.89 dB dynamic range for 16 ms frame shift size while consuming 9.3 $\mu$W. The measurement result verifies that the proposed IC performs a 12-class KWS task on the Google Speech Command Dataset (GSCD) with >86% accuracy and 12.4 ms latency. Comment: 14 pages, 21 figures, 2 tables
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::acedfa994012afb34344afba6b926344 https://doi.org/10.1109/jssc.2022.3195610 Zobrazit plný text záznamu