Automation of dictation exercises A working combination of CALL and NLP
نویسندگان
چکیده
This article is in the context of the Computer-Assisted Language Learning (CALL) framework, and addresses more specifically the automation of dictation exercises. It presents a method for correcting learners’ copies. Based around Natural Language Processing (NLP) tools, this method is original in two respects. First, it exploits the composition of finite-state machines, to both detect and delimit the errors. Second, it uses automatic morpho-syntactic analysis of the original dictation, which makes it easier to produce superficial and in-depth linguistic feedbacks. The system has been evaluated on a corpus of 115 copies including 1,532 copy errors. The accuracy of the error detection is 99%. The superficial feedback is 97.2% correct, the in-depth feedback, 96%, and the morpho-syntactic analysis, 87.7%.
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