Getting computers to talk like you and me
Getting computers to talk like you and me
Linguistic and pragmatic constraints on utterance interpretation
Linguistic and pragmatic constraints on utterance interpretation
A problem for RST: the need for multi-level discourse analysis
Computational Linguistics
Informational redundancy and resource bounds in dialogue
Informational redundancy and resource bounds in dialogue
A computational model for generating and interpreting indirect answers
A computational model for generating and interpreting indirect answers
Plan Recognition in Natural Language Dialogue
Plan Recognition in Natural Language Dialogue
Toward a computational theory of pragmatics--discourse, presupposition, and implicature
Toward a computational theory of pragmatics--discourse, presupposition, and implicature
Planning text for advisory dialogues: capturing intentional and rhetorical information
Computational Linguistics
A plan-based analysis of indirect speech acts
Computational Linguistics
Exploiting conversational implicature for generating concise explanations
EACL '91 Proceedings of the fifth conference on European chapter of the Association for Computational Linguistics
Discourse relations and defeasible knowledge
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Inferring discourse relations in context
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
Planning coherent multisentential text
ACL '88 Proceedings of the 26th annual meeting on Association for Computational Linguistics
Social goals in conversational cooperation
SIGDIAL '00 Proceedings of the 1st SIGdial workshop on Discourse and dialogue - Volume 10
Argumentation in artificial intelligence
Artificial Intelligence
"Was it good? It was provocative." Learning the meaning of scalar adjectives
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Predicting the uncertainty of sentiment adjectives in indirect answers
Proceedings of the 20th ACM international conference on Information and knowledge management
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This paper presents an implemented computational model for interpreting and generating indirect answers to yes-no questions in English. Interpretation and generation are treated, respectively, as recognition of and construction of a responder's discourse plan for a full answer. An indirect answer is the result of the responder providing only part of the planned response, but intending for his discourse plan to be recognized by the questioner. Discourse plan construction and recognition make use of shared knowledge of discourse strategies, represented in the model by discourse plan operators. In the operators, coherence relations are used to characterize types of information that may accompany each type of answer. Recognizing a mutually plausible coherence relation obtaining between the actual response and a possible direct answer plays an important role in recognizing the responder's discourse plan. During generation, stimulus conditions model a speaker's motivation for selecting a satellite. Also during generation, the speaker uses his own interpretation capability to determine what parts of the plan are inferable by the hearer and thus do not need to be explicitly given. The model provides wider coverage than previous computational models for generating and interpreting indirect answers and extends the plan-based theory of implicature in several ways.