A depthwise separable convolutional neural network for keyword spotting on an embedded system

A depthwise separable convolutional neural network for keyword spotting on an embedded system

Abstract A keyword spotting algorithm implemented on an embedded system using a depthwise separable convolutional neural network classifier is reported. The proposed system was derived from a high-complexity system with the goal to reduce complexity and to increase efficiency. In order to meet the r...

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Bibliographic Details
Main Authors: Peter Mølgaard Sørensen, Bastian Epp, Tobias May
Format: Article
Language:English
Published: SpringerOpen 2020-06-01
Series:EURASIP Journal on Audio, Speech, and Music Processing
Subjects:
Keyword spotting
Speech recognition
Embedded software
Deep learning
Convolutional neural networks
Quantization
Online Access:http://link.springer.com/article/10.1186/s13636-020-00176-2

Internet

http://link.springer.com/article/10.1186/s13636-020-00176-2

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