AIC Seminar Series

Natural language generators take application-specific domain representations as input, and need to formulate utterances that can convey this content to human users. To do this, generators must construct linguistic referring expressions to identify domain objects, select lexical items to express domain concepts, and use complex linguistic constructions to concisely convey related domain facts. In this talk, I argue that such problems are best solved through a uniform, comprehensive, declarative process. In our approach, the generator directly explores a search space for utterances described by a linguistic grammar. At each stage of search, the generator uses a model of interpretation, which characterizes the potential links between the utterance and the domain and context, to assess its progress in conveying domain-specific representations. Specifying choices in NLG is always a complex, labor-intensive process. In our approach, choices follow declaratively from syntactic, semantic and pragmatic characterizations of linguistic forms, and from formal models of domain context. Our declarative approach has supported the development of a detailed methodology for designing grammatical and conceptual resources which the generator can use to achieve desired output in a specified domain. In many cases, we can create resources automatically that will allow a generator to reproduce marked-up sample utterances.

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