Using a Tree-Adjoining Grammar in Translating English into Persian
Abstract
Increasing the domain of locality by using tree-adjoining-grammars (TAG) encouraged some researchers to use TAGs in applications such as machine translation, especially in the disambiguation process. Successful experiments of applying a TAG to French-English and KoreanEnglish translation encouraged us to use it for another language pairs with very divergent properties, i.e., English and Persian. By using a Synchronous TAG (S-TAG) for this pair of languages, we can benefit from syntactic and semantic features of these languages. In this paper, we report on our successful experiments of automatic translation of English into Persian. We also present a computational model for disambiguation of lexical selection, based on a decision tree approach. Finally, a new automatic method for learning a decision tree from a sample data set is introduced.
Keywords
natural language processing, machine translation, tree-adjoining-grammars, lexicalized grammar, English-Persian translation, decision-tree