Personality Recognition In Conversation

Personality recognition in dialogue is a subtask of natural language processing that aims to identify the personality traits of speakers by analyzing dialogue records. This task includes two scenarios: one-to-one and one-to-many dialogues. In the one-to-many dialogue scenario, the robot infers the speaker's personality trait vector by listening to conversations between the speaker and multiple parties, covering five dimensions: neuroticism, extraversion, openness, agreeableness, and conscientiousness. The goal is to enhance the personalized service level of dialogue systems and improve user experience, which has significant application value.