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

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