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首页> 外文期刊>Natural language engineering >A Tractable Hybrid Ddn-pomdp Approach To Affective Dialogue Modeling For Probabilisticframe-based Dialogue Systems
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A Tractable Hybrid Ddn-pomdp Approach To Affective Dialogue Modeling For Probabilisticframe-based Dialogue Systems

机译：基于概率框架的对话系统的情感对话建模的可操作混合Ddn-pomdp方法

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摘要

We propose a novel approach to developing a tractable affective dialogue model for probabilistic frame-based dialogue systems. The affective dialogue model, based on Partially Observable Markov Decision Process (POMDP) and Dynamic Decision Network (DDN) techniques, is composed of two main parts: the slot-level dialogue manager and the global dialogue manager. It has two new features: (1) being able to deal with a large number of slots and (2) being able to take into account some aspects of the user's affective state in deriving the adaptive dialogue strategies. Our implemented prototype dialogue manager can handle hundreds of slots, where each individual slot might have hundreds of values. Our approach is illustrated through a route navigation example in the crisis management domain. We conducted various experiments to evaluate our approach and to compare it with approximate POMDP techniques and handcrafted policies. The experimental results showed that the DDN-POMDP policy outperforms three handcrafted policies when the user's action error is induced by stress as well as when the observation error increases. Further, performance of the one-step look-ahead DDN-POMDP policy after optimizing its internal reward is close to state-of-the-art approximate POMDP counterparts.
机译：我们提出了一种新颖的方法来开发基于概率框架的对话系统的易处理的情感对话模型。基于部分可观察的马尔可夫决策过程（POMDP）和动态决策网络（DDN）技术的情感对话模型由两个主要部分组成：插槽级对话管理器和全局对话管理器。它具有两个新功能：（1）能够处理大量的时间片；（2）在推导自适应对话策略时，能够考虑用户情感状态的某些方面。我们实现的原型对话管理器可以处理数百个插槽，每个插槽可能具有数百个值。通过危机管理领域中的路线导航示例来说明我们的方法。我们进行了各种实验来评估我们的方法，并将其与近似的POMDP技术和手工制定的政策进行比较。实验结果表明，DDN-POMDP策略在压力导致用户的操作错误以及观察错误增加时，优于三种手工制定的策略。此外，优化其内部奖励后，一步向前的DDN-POMDP策略的性能接近于最新的近似POMDP对应对象。

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