A Real-time Voice Interface for Intelligent Wheelchairs
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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
This paper reports on the development of a real-time voice interface for navigation purposes of electric wheelchairs. To this end, we employ a convolutional neural network trained and fine-tuned using a small dataset that consists of Greek commands. Furthermore, the study explores a highly quantized version of the network to achieve computational efficiency while maintaining high accuracy on an edge device. The experimental results confirm the effectiveness of the model in accurately detecting keywords in real time with minimal misclassifications.
Description
CCS Concepts: Computing methodologies -> Speech recognition; Supervised learning by classification; Transfer learning; Computer systems organization -> Real-time system architecture; Hardware -> Hardware accelerators
@inproceedings{10.2312:imet.20231250,
booktitle = {International Conference on Interactive Media, Smart Systems and Emerging Technologies (IMET)},
editor = {Pelechano, Nuria and Liarokapis, Fotis and Rohmer, Damien and Asadipour, Ali},
title = {{A Real-time Voice Interface for Intelligent Wheelchairs}},
author = {Moschopoulos, Spyridon and Fudos, Ioannis and Koritsoglou, Kyriakos and Tatsis, Giorgos and Tzovaras, Dimitrios},
year = {2023},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-233-2},
DOI = {10.2312/imet.20231250}
}