Time-Encoded Mostly Digital Feature Extraction for Voice Activity Detection Tasks
Author:
Affiliation:
1. Carlos III University of Madrid,Electronics Technology Department,Madrid,Spain
2. Infineon Technologies,Power and Sensor Systems,Villach,Austria
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10557746/10557828/10558694.pdf?arnumber=10558694
Reference12 articles.
1. A 90 nm CMOS, Power-Proportional Acoustic Sensing Frontend for Voice Activity Detection
2. Design of an Always-On Deep Neural Network-Based 1-$\mu$ W Voice Activity Detector Aided With a Customized Software Model for Analog Feature Extraction
3. All-Digital VCO-ADC TAD Confirming Scaling and Stochastic Effects Using 16-nm FinFET CMOS
4. An 8 Bit 12.4 TOPS/W Phase-Domain MAC Circuit for Energy-Constrained Deep Learning Accelerators
5. A 23-μW Keyword Spotting IC With Ring-Oscillator-Based Time-Domain Feature Extraction
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