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MISC: A MIxed Strategy-Aware Model Integrating COMET for Emotional Support Conversation

About

Applying existing methods to emotional support conversation -- which provides valuable assistance to people who are in need -- has two major limitations: (a) they generally employ a conversation-level emotion label, which is too coarse-grained to capture user's instant mental state; (b) most of them focus on expressing empathy in the response(s) rather than gradually reducing user's distress. To address the problems, we propose a novel model \textbf{MISC}, which firstly infers the user's fine-grained emotional status, and then responds skillfully using a mixture of strategy. Experimental results on the benchmark dataset demonstrate the effectiveness of our method and reveal the benefits of fine-grained emotion understanding as well as mixed-up strategy modeling. Our code and data could be found in \url{https://github.com/morecry/MISC}.

Quan Tu, Yanran Li, Jianwei Cui, Bin Wang, Ji-Rong Wen, Rui Yan• 2022

Related benchmarks

TaskDatasetResultRank
Emotional Support ConversationESConv (test)
BLEU-214.5
44
Emotional Support ConversationExTES (test)
BLEU-213.8
15
Emotional Support ConversationESConv
Perplexity16.16
6
Emotional Support ConversationESConv
Fluency184
6
Response GenerationMI Counseling
Perplexity (PPL)14.33
5
Emotional Support Conversation GenerationESConv (test)
Accuracy31.34
5
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Code

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