DreamLLM-3D: Affective Dream Reliving using Large Language Model and 3D Generative AI
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arXiv
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| Format: | Preprint |
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2025
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| author | Liu, Pinyao Lee, Keon Ju Steinmaurer, Alexander Picard-Deland, Claudia Carr, Michelle Kitson, Alexandra |
| author_facet | Liu, Pinyao Lee, Keon Ju Steinmaurer, Alexander Picard-Deland, Claudia Carr, Michelle Kitson, Alexandra |
| contents | We present DreamLLM-3D, a composite multimodal AI system behind an immersive art installation for dream re-experiencing. It enables automated dream content analysis for immersive dream-reliving, by integrating a Large Language Model (LLM) with text-to-3D Generative AI. The LLM processes voiced dream reports to identify key dream entities (characters and objects), social interaction, and dream sentiment. The extracted entities are visualized as dynamic 3D point clouds, with emotional data influencing the color and soundscapes of the virtual dream environment. Additionally, we propose an experiential AI-Dreamworker Hybrid paradigm. Our system and paradigm could potentially facilitate a more emotionally engaging dream-reliving experience, enhancing personal insights and creativity. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_16439 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | DreamLLM-3D: Affective Dream Reliving using Large Language Model and 3D Generative AI Liu, Pinyao Lee, Keon Ju Steinmaurer, Alexander Picard-Deland, Claudia Carr, Michelle Kitson, Alexandra Human-Computer Interaction Artificial Intelligence Multimedia We present DreamLLM-3D, a composite multimodal AI system behind an immersive art installation for dream re-experiencing. It enables automated dream content analysis for immersive dream-reliving, by integrating a Large Language Model (LLM) with text-to-3D Generative AI. The LLM processes voiced dream reports to identify key dream entities (characters and objects), social interaction, and dream sentiment. The extracted entities are visualized as dynamic 3D point clouds, with emotional data influencing the color and soundscapes of the virtual dream environment. Additionally, we propose an experiential AI-Dreamworker Hybrid paradigm. Our system and paradigm could potentially facilitate a more emotionally engaging dream-reliving experience, enhancing personal insights and creativity. |
| title | DreamLLM-3D: Affective Dream Reliving using Large Language Model and 3D Generative AI |
| topic | Human-Computer Interaction Artificial Intelligence Multimedia |
| url | https://arxiv.org/abs/2503.16439 |