Visual isolated word recognition

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Visual isolated word recognition

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Title: Visual isolated word recognition
Author: Foo, Say Wei; Lim, Chee Chuan
Copyright year: 2009
Abstract: In this paper, the performance of neural network for isolated word recognition based on the movement of the mouth is investigated. Ten isolated words "zero" to "nine" form the vocabulary. The three parameters: height between the upper and lower lips, width of the mouth from left edge to right edge and the specific angle of the upper lip, are selected as representative features of the shape of the mouth. A oneagainst-the-rest neural network is used for classification. The architecture of the neural network consists of ten sub-units. Each sub-unit distinguishes 1 word from the other 9 and has 50 input vectors, 10 hidden nodes and 1 output neuron. By suitably combining the outcomes from the 3 features individually, 92.5% accuracy of recognition may be attained.
Type: Conference Paper
Conference name: IEEE International Conference on Information, Communications and Signal Processing (7th : 2009 : Macau)
Rights: © IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Version: Accepted version

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