Personality-affected Emotion Generation in Dialog Systems.

The article focuses on improving emotion generation in dialogue systems by considering personality traits, aiming to enhance user engagement and service quality. It mentions through the proposed task of Personality-affected Emotion Generation and the development of the Personality EmotionLines Dataset (PELD), the study addresses challenges in integrating personality and emotional factors while modeling personality as a transition weight, resulting in improved emotion generation performance.