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Sparse Binarization for Fast Keyword Spotting
Jonathan Svirsky
,
Uri Shaham
,
Ofir Lindenbaum
Bar-Ilan University - The Alexander Kofkin Faculty of Engineering
Department of Computer Science and Artificial Intelligence
Research output
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Contribution to journal
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Conference article
›
peer-review
Overview
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Computer Science
Neural Network Model
100%
Real-Time Application
100%
Linear Classifier
100%
Noisy Environment
100%
Computational Power
100%
Bandwidth Efficiency
100%
binarization
100%
Embedded System
100%
Keyphrases
Keyword Spotting
100%
Binarization
100%
Edge Devices
50%
Significant Benefit
25%
Increasing Prevalence
25%
Noisy Environment
25%
Computational Power
25%
Embedded Systems
25%
Neural Network Model
25%
Input Representation
25%
Bandwidth Utilization
25%
Sparse Input
25%
Time Application
25%
Linear Classifier
25%
Application Efficiency
25%
Computational Memory
25%
Compatible Model
25%
Smartphone System
25%
Voice-activated
25%