DocumentCode :
3206015
Title :
A neuro-hierarchial multilayer network in the translation of the American sign language
Author :
Abdallah, Moussa
Author_Institution :
Dept. of Electron. Eng., Princess Sumaya Univ., Amman, Jordan
fYear :
1998
fDate :
24-26 Apr 1998
Firstpage :
224
Lastpage :
227
Abstract :
A neuro hierarchial approach based on an adaptive back-propagation algorithm is proposed. In a separate preprocessing step, the input and the output vector are generated using the encoded-sequence representation. The algorithm is applied to translate the American sign language from spoken words. Experimental results indicate that this approach results in fast convergence, stable learning and a relatively small network size when compared to traditional methods
Keywords :
adaptive signal processing; backpropagation; biocommunications; language translation; multilayer perceptrons; pattern classification; speech recognition; American sign language; adaptive back-propagation algorithm; convergence; encoded-sequence representation; input vector; network size; neuro-hierarchial approach; neuro-hierarchial multilayer network; output vector; preprocessing step; spoken words; stable learning; translation; Computational efficiency; Computer architecture; Computer networks; Convergence; Data preprocessing; Error correction; Handicapped aids; Intelligent networks; Nonhomogeneous media; Object recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Southeastcon '98. Proceedings. IEEE
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4391-3
Type :
conf
DOI :
10.1109/SECON.1998.673334
Filename :
673334
Link To Document :
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