Transition network grammars for natural language analysis
Communications of the ACM
Exploiting the student model to emphasize language teaching pedagogy in natural language processing
ASSESSEVALNLP '99 Proceedings of a Symposium on Computer Mediated Language Assessment and Evaluation in Natural Language Processing
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This paper describes an implemented, prototype system for a sophisticated, intelligent tutor for instruction in a foreign language. The system is an application of artificial intelligence research in natural language, but it implements several ideas that depart from standard approaches to natural language understanding. For instance, the semantic analyzer diagnoses several kinds of comprehension problems and semantic errors that a student might make. Some fine distinctions in meaning are represented to detect misuse of words. Not only is a model of good syntax included in the tutor, but also a model of incorrect forms, rich enough to pinpoint specific syntactic mistakes. Finding the intended interpretation is complicated by the likelihood of student errors. Therefore, perfect syntactic form is not necessary for semantic analysis of the student's input. The problems discussed and solutions presented are closely related to the more general problem of how to respond to a natural language input that surpasses the computer's model of language or of context.