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TFSM‐based dialogue management model framework for affective dialogue systems
Author(s) -
Ren Fuji,
Wang Yu,
Quan Changqin
Publication year - 2015
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.22100
Subject(s) - computer science , partially observable markov decision process , inference , state (computer science) , process (computing) , artificial intelligence , observable , finite state machine , transition (genetics) , machine learning , markov chain , markov model , algorithm , biochemistry , chemistry , physics , quantum mechanics , gene , operating system
A new dialogue management model for affective dialogue system, which aims to provide a service of information inquiry and affective interaction, is proposed in this paper. First, we construct two finite state machines (TFSM) to model the user and the system, respectively, and simulate the dialogue process as an information exchange between the two state machines. All possible state transitions in dialogue and its probabilities of the user are summarized as a user model, which is helpful for the system to inference and predict the user's internal states. Second, we further discuss the implementation methods of information inquiry and emotional response modules. Finally, we employ the return function of partially observable Markov decision processes (POMDP) model to analyze and evaluate the TFSM‐based dialogue management model. The experimental results not only show the relationships between the average returns, recognition error rates, and state transition probabilities but also confirm that our TFSM‐based dialogue management model outperforms the conventional FSM model. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.