IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Online ISSN : 1745-1337
Print ISSN : 0916-8508
Regular Section
Improving the Recognition Accuracy of a Sound Communication System Designed with a Neural Network
Kosei OZEKINaofumi AOKISaki ANAZAWAYoshinori DOBASHIKenichi IKEDAHiroshi YASUDA
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2021 Volume E104.A Issue 11 Pages 1577-1584

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Abstract

This study has developed a system that performs data communications using high frequency bands of sound signals. Unlike radio communication systems using advanced wireless devices, it only requires the legacy devices such as microphones and speakers employed in ordinary telephony communication systems. In this study, we have investigated the possibility of a machine learning approach to improve the recognition accuracy identifying binary symbols exchanged through sound media. This paper describes some experimental results evaluating the performance of our proposed technique employing a neural network as its classifier of binary symbols. The experimental results indicate that the proposed technique may have a certain appropriateness for designing an optimal classifier for the symbol identification task.

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