Visual isolated word recognition

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...

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Bibliographic Details
Main Authors: Foo, Say Wei, Lim, Chee Chuan
Other Authors: IEEE International Conference on Information, Communications and Signal Processing (7th : 2009 : Macau)
Format: Conference or Workshop Item
Language:English
Published: 2009
Online Access:https://hdl.handle.net/10356/91589
http://hdl.handle.net/10220/4614
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Institution: Nanyang Technological University
Language: English
Description
Summary: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.