Visual information is an important part of human perception, yet visually challenged people experience significant difficulties in acquiring and processing visual content. This study introduces “Sound Vision” (SV), an innovative system that uses cutting-edge AI-driven technology to translate pictures into aural representations, therefore improving accessibility for those with visual impairments. SV uses computer vision (CV) methods for image processing and merges the Raspberry Pi’s audio synthesis capabilities to provide visually impaired people with an aural interpretation of their environment. We go into the technical components of the Sound Vision system in this section, discussing the image processing algorithms for object detection and scene interpretation, as well as the use of Raspberry Pi for audio synthesis to produce meaningful soundscapes. The study also goes into the practical uses of Sound Vision, such as navigational help, item identification, and the potential to improve the overall quality of life for visually impaired people. Sound Vision’s usefulness is proved through user tests and evaluations with visually impaired participants, showing the system’s ability to provide vital audio input. This enables visually impaired people to achieve independence and a better awareness of their surroundings, so increasing their overall quality of life.