ESCoT: Towards Interpretable Emotional Support Dialogue Systems

التفاصيل البيبلوغرافية
العنوان: ESCoT: Towards Interpretable Emotional Support Dialogue Systems
المؤلفون: Zhang, Tenggan, Zhang, Xinjie, Zhao, Jinming, Zhou, Li, Jin, Qin
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computation and Language
الوصف: 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 $\href{https://github.com/TeigenZhang/ESCoT}{https://github.com/TeigenZhang/ESCoT}$.
Comment: Accepted to ACL 2024 (Long Paper)
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2406.10960
رقم الأكسشن: edsarx.2406.10960
قاعدة البيانات: arXiv