FADO: Feedback-Aware Double COntrolling Network for Emotional Support Conversation

• URL: http://arxiv.org/abs/2211.00250v1
• Date: Tue, 1 Nov 2022 03:37:30 GMT
• Title: FADO: Feedback-Aware Double COntrolling Network for Emotional Support Conversation
• Authors: Wei Peng, Ziyuan Qin, Yue Hu, Yuqiang Xie, Yunpeng Li
• Abstract summary: We propose a Feedback-Aware Double COntrolling Network (FADO) to make a strategy schedule and generate the supportive response. Experimental results on ESConv show that the proposed FADO has achieved the state-of-the-art performance in terms of both strategy selection and response generation.
• Score: 15.739642511241158
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Emotional Support Conversation (ESConv) aims to reduce help-seekers'emotional distress with the supportive strategy and response. It is essential for the supporter to select an appropriate strategy with the feedback of the help-seeker (e.g., emotion change during dialog turns, etc) in ESConv. However, previous methods mainly focus on the dialog history to select the strategy and ignore the help-seeker's feedback, leading to the wrong and user-irrelevant strategy prediction. In addition, these approaches only model the context-to-strategy flow and pay less attention to the strategy-to-context flow that can focus on the strategy-related context for generating the strategy-constrain response. In this paper, we propose a Feedback-Aware Double COntrolling Network (FADO) to make a strategy schedule and generate the supportive response. The core module in FADO consists of a dual-level feedback strategy selector and a double control reader. Specifically, the dual-level feedback strategy selector leverages the turn-level and conversation-level feedback to encourage or penalize strategies. The double control reader constructs the novel strategy-to-context flow for generating the strategy-constrain response. Furthermore, a strategy dictionary is designed to enrich the semantic information of the strategy and improve the quality of strategy-constrain response. Experimental results on ESConv show that the proposed FADO has achieved the state-of-the-art performance in terms of both strategy selection and response generation. Our code is available at https://github/after/reviewing.

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