Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/91589
Title: Visual isolated word recognition
Authors: Foo, Say Wei
Lim, Chee Chuan
Issue Date: 2009
Source: Foo, S. W., & Lim, C. C. Visual isolated word reconition. International Conference on Information, Communications & Signal Processing (pp.1-4).
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.
URI: https://hdl.handle.net/10356/91589
http://hdl.handle.net/10220/4614
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Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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