AI-Based Dream Pattern Decoder Using Jung and Freud Theory

Abstract

Dreams have always offered a mysterious look into the human mind, inspiring both curiosity and research. This study presents a computational approach to interpreting dream narratives by combining artificial intelligence with classical psychoanalytic concepts proposed by Sigmund Freud and Carl Jung. Using natural language processing techniques, the system analyses written dream reports to identify recurring themes, emotions, and symbolic patterns that reflect personal and collective psychological meanings. Freud’s idea of manifest and latent content helps uncover hidden desires and suppressed emotions, while Jung’s archetype framework supports the recognition of universal symbols such as Shadow, Anima, or Self. The model was trained and evaluated on dream-related datasets to examine its ability to extract psychological insights similar to those derived from expert interpretations. The findings suggest that AI-based interpretation can complement traditional psychoanalysis by offering a consistent, data-driven, and scalable tool for research and mental health applications. This work highlights how technology can enhance our understanding of the subconscious mind and expand the possibilities of psychological exploration in modern contexts.