Oct 27, 2021 · This work analyzes the challenges, benefits, and drawbacks of the different execution modes available for TCN-based KWS inference on dedicated ...
This work analyzes the challenges, benefits, and drawbacks of the different execution modes available for TCN-based KWS inference on dedicated hardware.
... Although there are no standard benchmarks or datasets for TCNs, we can compare the average energy efficiency over an inference for stateof-the-art designs.
Efficient Execution of Temporal Convolutional Networks for Embedded Keyword Spotting. Author: Giraldo, JSP. Jain, Vikram ; Verhelst, Marian. Keywords: Science ...
Apr 8, 2019 · In this paper, we propose a temporal convolution for real-time KWS on mobile devices. Unlike most of the 2D convolution-based KWS approaches ...
Article "Efficient Execution of Temporal Convolutional Networks for Embedded Keyword Spotting" Detailed information of the J-GLOBAL is an information ...
[IEEE] Efficient Execution of Temporal Convolutional Networks for Embedded Keyword Spotting ... Article Source：Institute of Electrical and Electronics Engineers ...
Efficient Execution of Temporal Convolutional Networks for Embedded Keyword Spotting. Article. Dec 2021. J. S. P. Giraldo · Vikram Jain ...
FPGA Implementation of Keyword Spotting System Using Depthwise ...
www.ncbi.nlm.nih.gov › PMC10303093
Jun 19, 2023 · In this paper, we propose a depthwise separable binarized/ternarized neural network (DS-BTNN) hardware accelerator capable of performing both WUW recognition ...
Sep 20, 2023 · This paper proposes a resource-efficient keyword spotting (KWS) system based on a convolutional neural network (CNN).