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ITR/PE+SY:Mapping Meetings: Language Technology to make Sense of Human Interaction

ITR/PE+SY:Mapping Meetings: Language Technology to make Sense of Human Interaction
ITR/PE SY:映射会议:理解人类互动的语言技术
批准号:
0121396
负责人:
Nelson Morgan
金额:
$140.29万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2001
资助国家:
美国
项目状态:
已结题
起止时间:
2001-09-01 至 2006-02-28

项目摘要

项目成果

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中文摘要
翻译
会议是几乎每个企业必不可少的持续流程。记录会议是为了提供人类互动的历史。然而,仍然存在两个核心挑战:(1)如何理解这些会议中的群体动态;(2)如何搜索这些互动的历史,以找到可能需要的信息。本研究旨在开发基于“会议地图”隐喻的自动信息处理系统,会议地图是一种结构化表示,支持以不同规模呈现会议的多个视图。该项目将侧重于两大类地图:内容地图,描绘讨论的主题和作出的决定;互动地图,确定参与者的作用和关系以及协同程度。构建内容和交互地图将涉及从主题变化和显著性到分歧/共识的信息自动分类。 这些地图将用于生成简单的指示性摘要,现成的可视化工具将用于地图展示。 该项目将以100个小时会议的分析为基础。 评价将使用自动摘要的客观识别准确性和专家评估。会议地图尊重会议场景中存在的信息的多样性,并为人与人的交互提供有效的支持。
英文摘要
Meetings are essential and ongoing processes in almost every enterprise. To record meetings is to provide a history of human interactions. However, two central challenges remain: (1) how to make sense of the group dynamics in those meetings and (2) how to search through a history of those interactions to find the information one may want. This research aims to develop automatic information processing systems based on the metaphor of a "meeting map", a structured representation that supports the presentation of multiple views of a meeting at different scales. The project will focus on two broad map categories: content maps, portraying topics discussed and decisions made; and interaction maps, identifying the roles and relationships of the participants and the level of concurrence. Building content and interaction maps will involve automatic classification of information from topic changes and salience to disagreement/consensus. These maps will be used for generating simple indicative summaries, and off-the-shelf visualization tools will be used for map presentation. The project will build on analyses of 100 hours of meetings. Evaluations will use objective recognition accuracies and expert assessments of automatic summaries. Meeting maps respect the diversity of information present in meeting scenarios, and provide effective support for human-to-human interactions.
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会议论文
RI: Small: Collaborative Research: Towards Modeling Source Separation from Measured Cortical Responses
EAGER: Collaborative Research: Towards Modeling Human Speech Confusions in Noise
International: An Analysis of Speaker Diarization Systems Errors
CI-P: Towards a Consensus Representation for Understanding Structure of Multiparty Conversations
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