A novel factored POMDP model for affective dialogue management

A novel factored POMDP model for affective dialogue management
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一种新颖的情感对话管理因子 POMDP 模型

DOI:
10.3233/ifs-162126
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发表时间:
2016
影响因子:
2
通讯作者:
Quan Changqin
Quan Changqin
中科院分区:
计算机科学4区
文献类型:
--
作者:
Ren Fuji;Wang Yu;Quan Changqin

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部分可观测马尔可夫决策过程(POMDP)模型已多次被证明适用于健壮的口语对话管理。目前,POMDP模型的一些分解表示是针对特定的对话任务而设计的。本文提出了一种新的POMDP模型来描述情感对话管理的新应用。与已有模型不同,该模型将用户的状态空间和系统的观察空间划分为目标和情感两个不同的组成部分。此外,系统的动作空间首次被分解为两部分,即目标反应和情感反应,相应地,奖励函数通过两部分奖励的加权和来更新。并以智能音乐播放器为例,说明了如何应用该模型构建情感对话系统。设计了四个实验来揭示关键参数对系统性能的影响。仿真结果验证了该模型的合理性和可行性。
Partially observable Markov decision process (POMDP) model has been demonstrated many times to be suited for robust spoken dialogue management. Recently, some factored representations of POMDP model are designed for specific dialogue tasks. This paper proposes a novel factored POMDP model to describe a new application of affective dialogue management. Different from existing models, the user's state space and the system's observation space are both divided into two distinct components: goal and emotion. Moreover, the system's action space is for the first time factored into two parts, i.e., goal response and emotion response, and the reward function is accordingly updated by weighted sum of the two-part rewards. An example of intelligent music player is given to explain how to apply the new model to build an affective dialogue system. Four experiments are designed to reveal the influence of key parameters on the system performance. The simulation results demonstrate the rationality and feasibility of the proposed model.
DOI: 10.1007/s10772-010-9068-y
发表时间: 2010-03
影响因子: --
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