Speaking aid using neural networks for the deaf

研究成果: 雜誌貢獻期刊論文同行評審

1 引文 斯高帕斯(Scopus)

摘要

In this paper, we propose to use two EMI-Gloves connected to an IBM compatible PC via Degraded HyperEllipsoidal Composite Neural Networks (DHECNNs) to implement a prototype speaking aid for the deaf or non-vocal persons. Using a special learning scheme, the DHECNNs can quickly learn the complex mapping of measurements of ten fingers' flex angles to corresponding categories. The prototype speaking aid is evaluated for the classification of 51 static hand gestures from 4 'speakers'. The recognition accuracy for the testing set is 92.3%.

原文???core.languages.en_GB???
頁(從 - 到)351-357
頁數7
期刊Biomedical Engineering - Applications, Basis and Communications
8
發行號4
出版狀態已出版 - 1 1月 1996

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