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}.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Emotional Support Conversation | ESConv (test) | BLEU-214.5 | 44 | |
| Emotional Support Conversation | ExTES (test) | BLEU-213.8 | 15 | |
| Emotional Support Conversation | ESConv | Perplexity16.16 | 6 | |
| Emotional Support Conversation | ESConv | Fluency184 | 6 | |
| Response Generation | MI Counseling | Perplexity (PPL)14.33 | 5 | |
| Emotional Support Conversation Generation | ESConv (test) | Accuracy31.34 | 5 |