Computer Science > Human-Computer Interaction
[Submitted on 19 Nov 2020 (v1), last revised 5 Oct 2021 (this version, v2)]
Title:Towards Emotion-Aware User Simulator for Task-Oriented Dialogue
View PDFAbstract:The performance of a task-completion dialogue agent usually affects the user experience: when the conversation system yields an unreasonable response, users may feel dissatisfied. Besides, early termination often occurs in disappointing conversations. However, existing off-the-shelf user simulators generally assume an ideal and cooperative user, which is somewhat different from a real user, and inevitably lead to a sub-optimal dialogue policy. In this paper, we propose an emotion-aware user simulation framework for task-oriented dialogue, which is based on the OCC emotion model to update user emotions and drive user actions, to generate simulated behaviors that more similar to real users. We present a linear implementation (The source code will be released soon.) that is easy to understand and extend, and evaluate it on two domain-specific datasets. The experimental results show that the emotional simulation results of our proposed framework conform to common sense and have good versatility for different domains. Meanwhile, our framework provides us with another perspective to understand the improvement process of the dialogue policy model based on reinforcement learning.
Submission history
From: Rui Zhang [view email][v1] Thu, 19 Nov 2020 07:21:07 UTC (2,493 KB)
[v2] Tue, 5 Oct 2021 03:37:53 UTC (560 KB)
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