Do You Know My Emotion? Emotion-Aware Strategy Recognition towards a Persuasive Dialogue System

Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Yajing Sun
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引用次数: 2

Abstract

Persuasive strategy recognition task requires the system to recognize the adopted strategy of the persuader according to the conversation. However, previous methods mainly focus on the contextual information, little is known about incorporating the psychological feedback, i.e. emotion of the persuadee, to predict the strategy. In this paper, we propose a Cross-channel Feedback memOry Network (CFO-Net) to leverage the emotional feedback to iteratively measure the potential benefits of strategies and incorporate them into the contextual-aware dialogue information. Specifically, CFO-Net designs a feedback memory module, including strategy pool and feedback pool, to obtain emotion-aware strategy representation. The strategy pool aims to store historical strategies and the feedback pool is to obtain updated strategy weight based on feedback emotional information. Furthermore, a cross-channel fusion predictor is developed to make a mutual interaction between the emotion-aware strategy representation and the contextual-aware dialogue information for strategy recognition. Experimental results on \textsc{PersuasionForGood} confirm that the proposed model CFO-Net is effective to improve the performance on M-F1 from 61.74 to 65.41.
你知道我的情绪吗?说服性对话系统的情绪感知策略识别
说服策略识别任务要求系统根据对话来识别说服者所采用的策略。然而,以往的方法主要集中在语境信息上,很少有人知道如何结合心理反馈,即被说服者的情绪来预测策略。在本文中,我们提出了一个跨渠道反馈记忆网络(CFO-Net)来利用情绪反馈迭代测量策略的潜在利益,并将其纳入上下文感知对话信息。具体而言,CFO-Net设计了一个反馈记忆模块,包括策略池和反馈池,以获得情绪感知的策略表示。策略池用于存储历史策略,反馈池用于根据反馈的情绪信息获取更新的策略权重。在此基础上,提出了一种跨通道融合预测器,在情感感知策略表示和上下文感知对话信息之间进行交互,实现策略识别。在\textsc{PersuasionForGood}上的实验结果证实了所提出的模型CFO-Net可以有效地将M-F1的性能从61.74提高到65.41。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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