Beyond Descriptions: A Generative Scene2Audio Framework for Blind and Low-Vision Users to Experience Vista Landscapes
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Abstract (arXiv)
Current scene perception tools for Blind and Low Vision (BLV) individuals rely on spoken descriptions but lack engaging representations of visually pleasing distant environmental landscapes (Vista spaces). Our proposed Scene2Audio framework generates comprehensible and enjoyable nonverbal audio using generative models informed by psychoacoustics, and principles of scene audio composition. Through a user study with 11 BLV participants, we found that combining the Scene2Audio sounds with speech creates a better experience than speech alone, as the sound effects complement the speech making the scene easier to imagine. A mobile app "in-the-wild" study with 7 BLV users for more than a week further showed the potential of Scene2Audio in enhancing outdoor scene experiences. Our work bridges the gap between visual and auditory scene perception by moving beyond purely descriptive aids, addressing the aesthetic needs of BLV users.
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References · 9
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
- 2018The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scalecited by 542
- 2022I Hear Your True Colors: Image Guided Audio Generationcited by 92
- 2024Design Principles for Generative AI Applicationscited by 57
- 2024Investigating Use Cases of AI-Powered Scene Description Applications for Blind and Low Vision Peoplecited by 24
- 2024PicoAudio: Enabling Precise Timestamp and Frequency Controllability of Audio Events in Text-to-audio Generationcited by 12
- 2023Understanding Visual Arts Experiences of Blind Peoplecited by 9
- 2024MorphFader: Enabling Fine-grained Controllable Morphing with Text-to-Audio Modelscited by 4
- 2023Example-Based Framework for Perceptually Guided Audio Texture Generationcited by 1
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