A Frame-Based Probabilistic Framework for Spoken Dialog Management Using Dialog Examples

A Frame-Based Probabilistic Framework for Spoken Dialog Management Using Dialog Examples
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使用对话示例进行口语对话管理的基于框架的概率框架

DOI:
10.3115/1622064.1622088
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发表时间:
2008
期刊:
2008 IEEE Spoken Language Technology Workshop
影响因子:
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通讯作者:
G. G. Lee
G. G. Lee
中科院分区:
--
文献类型:
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作者:
Kyungduk Kim;Cheongjae Lee;Sangkeun Jung;G. G. Lee

文献摘要

被引文献

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本文提出了一个概率框架,口语对话管理使用对话的例子。为了克服经典的部分可观察马尔可夫决策过程(POMDPs)的对话管理器的复杂性问题,我们使用基于帧的信念状态表示,降低了信念更新的复杂性。我们还使用对话框示例来维护合理数量的系统操作,以降低优化策略的复杂性。我们开发了天气信息和汽车导航对话系统,采用基于帧的概率框架。该框架使人们能够使用概率方法开发口语对话系统,而没有POMDP的复杂性问题。
This paper proposes a probabilistic framework for spoken dialog management using dialog examples. To overcome the complexity problems of the classic partially observable Markov decision processes (POMDPs) based dialog manager, we use a frame-based belief state representation that reduces the complexity of belief update. We also used dialog examples to maintain a reasonable number of system actions to reduce the complexity of the optimizing policy. We developed weather information and car navigation dialog system that employed a frame-based probabilistic framework. This framework enables people to develop a spoken dialog system using a probabilistic approach without complexity problem of POMDP.