Computational Models of Dialogue: Speech-Act Theory Meets Real Utterances

对话的计算模型：言语行为理论与真实话语的结合

• 批准号: 9110797
• 负责人: David Novick
• 金额: $ 6.76万
• 依托单位: Oregon Graduate Institute of Science & Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-09-01 至 1994-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9110797&HistoricalAwards=false
• 关键词: Computational; Models; Dialogue; Speech; Act

This is a Research Initiation Award (RIA). The research aims at resolving long-standing problems with the use of speech-act theory in computational systems for natural language understanding and to provide methods of interpreting unconstrained discourse. The integration of verbal and non- verbal speech acts are still very poorly understood and is critical for human-computer interactions. This research seeks to integrate many modalities with the study of speech acts, an important conceptual framework in speech and dialog processes. The goals are: (1) to determine how the theory of meta-acts can be extended and refined to model negotiations of reference and confirmation of mutuality of knowledge, and (2) to determine if meta-act models can be validated predictively. Meta-knowledge models include information about conversations that are non- verbal, such as turn-taking. The project derives meta-acts as a rational strategy of action, given attributions of the participants' beliefs, goals and expectations at the point in the dialogue in which the acts actually occur. The acts are then expressed in a rule-based simulation of similar conversations. A byproduct of the research is a database of analyzed and transcribed data useful for other researchers. It is expected that there will be substantial impact in human-computer interactions research and aspects of research in speech and natural language processing.

这是一个研究启动奖（RIA）。 本研究旨在 用言语行为解决长期存在的问题 自然语言计算系统理论 理解并提供解释方法 不受约束的话语 语言与非语言的融合 言语行为仍然知之甚少， 对人机交互至关重要。 这项研究旨在 将多种模态与言语行为研究相结合， 语音和对话过程中重要的概念框架。 目的是：（1）确定元行为理论如何能够 扩展和完善，以示范参考谈判， （2）确定是否存在知识的相互性; 元行为模型可以被预测性地验证。 元知识 模型包括关于非- 口头的，如轮流。 该项目将元行为作为 合理的行动策略，鉴于属性的 参与者的信念、目标和期望， 对话中的行为实际发生。 然后， 在类似对话的基于规则的模拟中表达。 一 研究的副产品是一个分析和 转录的数据对其他研究人员有用。 预计 这将对人机交互产生重大影响， 互动研究和语音研究方面， 自然语言处理。