E-Content Based UNL Deconverter Framework for Tamil and Hindi Language
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Abstract
The enormous growth in E-content information in the web requires the content to be available in the natural language. The demand in converting the E-content from the one natural language to another natural language have been increased recently. E-content information was obtained in the target language from the Interlingua representation such as Universal Networking Language (UNL) rather than from the source language. A framework towards conversion of a UNL expression related E-content into the tamil and hindi language was presented in this paper. This approach uses the dictionary to select target language words for UWs in the UNL expression. The morphological rules were created to modify the headwords owing to the target language. Also the Hidden Markov Model technique has been adopted to define the word order in the generated sentence.
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Keywords: E-content, tamil, hindi, deconverter, dictionary, morphological rules, Hidden Markov Model.
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