Abstract
Any-Language Communications has developed a novel semantics-oriented pre-market prototype system, based on the Theory of Universal Grammar, that uses the innate relationships of the words in a sensible sentence (the natural intelligence) to determine the true contextual meaning of all the words. The system is built on a class/category structure of language concepts and includes a weighted inheritance system, a number language word conversion, and a tailored genetic algorithm to select the best of the possible word meanings. By incorporating all of the language information within the dictionaries, the same semantic processing code is used to interpret any language. This approach is suitable for machine translation (MT), sophisticated text mining, and artificial intelligence applications. An MT system has been tested with English, French, German, Hindi, and Russian. Sentences for each of those languages have been successfully interpreted and proper translations generated.
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© 2002 Springer-Verlag Berlin Heidelberg
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Bender, H.J. (2002). Natural Intelligence in a Machine Translation System. In: Richardson, S.D. (eds) Machine Translation: From Research to Real Users. AMTA 2002. Lecture Notes in Computer Science(), vol 2499. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45820-4_24
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DOI: https://doi.org/10.1007/3-540-45820-4_24
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44282-0
Online ISBN: 978-3-540-45820-3
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