Machine Translation, Does it Have Anything to Do with Foriegn Language Education?
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Abstract
Machine translation (MT) is a computational representation of linguistic knowledge database as to how the human language would work and how humans process the languages. One widely-accepted linguistic framework is a rule-based lexical theory where learners process languages primarily from lexical information supplied by individual words and syntactic rules. This paper aims to illustrate such an MT system, and attempts to map the flow of processes out to the humans' learning of foreign languages. The theory of linguistics is still a long way ahead to provide any definite nature of human language. However, MT can provide a basis for hypothesis testing of human language learning. The paper will demonstrate an MT system based on Lexical-Functional Grammar (LFG) framework, and compare the steps of procedure with foreign language learning. The complexity of human language requires equally complex system of processing human languages. The paper will show a plethora of decisions made by the MT system which essentially represents human solutions of language processing.
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