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Towards processing Arabic minimal syllable automatically
Mohammed Dib1.
The purpose of this paper is to try to treat the Arabic minimal syllable automatically, so as to use
Arabic in the field of artificial intelligence. To this effect three technological tools are used; Gold
wave ,SFS (Speech Filing System), and Neural Net Works to recognize automatically the
minimal syllable located in first, mid, and final position of three Arabic words recorded by forty
Algerian speakers of different age and sex. Eight experiments have been done in this work
where the sounds have been recorded in Gold wave and treated in SFS and trained in NNW. The
result show that The optimal neural net work is that of non- ordered data with one layer, five
nodes and 150 steps because it has given an error rate of 0.0032.The findings suggest the
application of this type of neural net works in all syllables and all languages too because the
same principle can be used in all languages.
Affiliation:
- University of Mascara, Algeria
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