Knowledge Enhanced Reflection Generation for Counseling Dialogues
Siqi Shen, Verónica Pérez‐Rosas, CHARLES A. WELCH, Soujanya Poria, Rada F. Mihalcea · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · 2022
In this paper, we study the effect of commonsense and domain knowledge while generating responses in counseling conversations using retrieval and generative methods for knowledge integration.We propose a pipeline that collects domain knowledge through web mining, and show that retrieval from both domainspecific and commonsense knowledge bases improves the quality of generated responses.We also present a model that incorporates knowledge generated by COMET using soft positional encoding and masked self-attention.We show that both retrieved and COMETgenerated knowledge improve the system's performance as measured by automatic metrics and by human evaluation.Lastly, we present a comparative study on the types of knowledge encoded by our system, showing that causal and intentional relationships benefit the generation task more than other types of commonsense relations.