With the rapid development of artificial intelligence, especially natural language processing, dialogue systems are widely used in customer service, virtual assistants, education, and counseling. However, existing systems struggle to reflect users’ personality traits, limiting personalization. This study integrates the Big Five traits into dialogue generation by extracting linguistic features and training models to produce personality-aligned responses. The resulting system improves naturalness and personalization, offering more human-like interactions and contributing to both NLP and personality psychology research.