以数据为中心的架构中的持久信息状态

SIGDIAL Workshop Pub Date : 2008-06-19 DOI:10.3115/1622064.1622076

S. Varges, G. Riccardi, S. Quarteroni

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引用次数: 16

摘要

我们提出了以ADAMACH数据为中心的对话系统，该系统允许在对话内部和对话之间对对话上下文、语音识别结果和其他系统生成的表示进行在线和离线挖掘。该体系结构实现了语音和语言处理的“胖管道”。我们详细介绍了该方法如何基于大学Helpdesk领域的用户研究集成领域知识和不断发展的经验数据。

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Persistent Information State in a Data-Centric Architecture

We present the ADAMACH data centric dialog system, that allows to perform on- and off-line mining of dialog context, speech recognition results and other system-generated representations, both within and across dialogs. The architecture implements a "fat pipeline" for speech and language processing. We detail how the approach integrates domain knowledge and evolving empirical data, based on a user study in the University Helpdesk domain.

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SIGDIAL Workshop

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