ESCoT: Towards Interpretable Emotional Support Dialogue Systems

TL;DR

This paper introduces ESCoT, a novel framework for emotional support dialogue systems that emphasizes interpretability by mimicking emotional understanding and regulation processes, supported by a new dataset and model.

Contribution

The paper proposes ESCoT, a new interpretable response generation scheme, and constructs a dataset with chains of emotional reasoning for support dialogues.

Findings

ESCoT improves interpretability of support responses.

Human evaluations favor ESCoT-generated responses.

The dataset enables better emotional reasoning in dialogue systems.

Abstract

Understanding the reason for emotional support response is crucial for establishing connections between users and emotional support dialogue systems. Previous works mostly focus on generating better responses but ignore interpretability, which is extremely important for constructing reliable dialogue systems. To empower the system with better interpretability, we propose an emotional support response generation scheme, named $\textbf{E}$motion-Focused and $\textbf{S}$trategy-Driven $\textbf{C}$hain-$\textbf{o}$f-$\textbf{T}$hought ($\textbf{ESCoT}$), mimicking the process of $\textit{identifying}$, $\textit{understanding}$, and $\textit{regulating}$ emotions. Specially, we construct a new dataset with ESCoT in two steps: (1) $\textit{Dialogue Generation}$ where we first generate diverse conversation situations, then enhance dialogue generation using richer emotional support strategies based on these situations; (2) $\textit{Chain Supplement}$ where we focus on supplementing selected dialogues with elements such as emotion, stimuli, appraisal, and strategy reason, forming the manually verified chains. Additionally, we further develop a model to generate dialogue responses with better interpretability. We also conduct extensive experiments and human evaluations to validate the effectiveness of the proposed ESCoT and generated dialogue responses. Our data and code are available at $\href{https://github.com/TeigenZhang/ESCoT}{https://github.com/TeigenZhang/ESCoT}$.