Improving Empathetic Dialogue Generation by Dynamically Infusing Commonsense Knowledge
In empathetic conversations, individuals express their empathy towards others. Previous work has mainly focused on generating empathetic responses by utilizing the speaker's emotion. Besides, external commonsense knowledge has been applied to enhance the system's understandings of the speaker's situation. However, given an event, commonsense knowledge base contains various relations, potentially leading to confusion for the dialogue system. Consequently, inconsistencies arise among the emotion, generated response and speaker's contextual information. To this end, we propose a novel approach for empathetic response generation, which incorporates an adaptive module for commonsense knowledge selection to ensure consistency between the generated empathetic responses and the speaker's situation. This selected knowledge is used to refine the commonsense cognition and empathy expression for generated responses. Experimental results show that our approach significantly outperforms baseline models in both automatic and human evaluations, exhibiting the generation of more coherent and empathetic responses. Moreover, case studies highlight the interpretability of knowledge selection in the responses and the effectiveness of adaptive module in our model. Code: https://github.com/Hanscal/DCKS.
Code (1)
Tasks
Dialogue GenerationEmpathetic Response GenerationResponse GenerationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Commonsense-Aware Prompting for Controllable Empathetic Dialogue Generation
Improving the emotional awareness of pre-trained language models is an emerging important problem for dialogue generation tasks. Although prior studies have introduced methods to improve empathetic dialogue generation, f…
Dialogue GenerationEmpathetic Dialogue Generation via Sensitive Emotion Recognition and Sensible Knowledge Selection
Empathy, which is widely used in psychological counselling, is a key trait of everyday human conversations. Equipped with commonsense knowledge, current approaches to empathetic response generation focus on capturing imp…
Dialogue GenerationEmotion RecognitionEmpathetic Response GenerationResponse GenerationCASE: Aligning Coarse-to-Fine Cognition and Affection for Empathetic Response Generation
Empathetic conversation is psychologically supposed to be the result of conscious alignment and interaction between the cognition and affection of empathy. However, existing empathetic dialogue models usually consider on…
Dialogue GenerationEmpathetic Response GenerationResponse GenerationEmpathetic Dialogue Generation with Pre-trained RoBERTa-GPT2 and External Knowledge
One challenge for dialogue agents is to recognize feelings of the conversation partner and respond accordingly. In this work, RoBERTa-GPT2 is proposed for empathetic dialogue generation, where the pre-trained auto-encodi…
DecoderDialogue GenerationCEM: Commonsense-aware Empathetic Response Generation
A key trait of daily conversations between individuals is the ability to express empathy towards others, and exploring ways to implement empathy is a crucial step towards human-like dialogue systems. Previous approaches …
Empathetic Response GenerationResponse Generation