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@article{204321,
        author = {Om Mane and Om ambekar and shruti gharpankar and madhura kadam and sneha kupate and V.B koli},
        title = {AI-Based Multimodal Communication App for People with Disabilities},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {1979-1982},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=204321},
        abstract = {People with speech and motor disabilities often face difficulties in expressing their needs and communicating effectively in daily life. Existing assistive communication systems are expensive, hardware dependent, and inaccessible for many users. This paper presents an AI-based multimodal communication application that combines text-to-speech conversion, webcam-based eye tracking, and an accessible user interface to support real-time communication. The system uses low-cost hardware and open-source technologies such as OpenCV and Media Pipe to provide an affordable and efficient assistive solution. The application offers typing mode, gaze-controlled interaction, customizable accessibility settings, and natural speech generation to improve user independence and communication efficiency. Experimental testing demonstrates reliable gaze detection, smooth text-to-speech output, and responsive interaction under standard conditions. The proposed system aims to promote inclusivity and improve the quality of life for individuals with disabilities.},
        keywords = {Assistive Technology, Eye Tracking, Text-to-Speech, Accessibility, Artificial Intelligence, Human Computer Interaction, OpenCV, Media Pipe.},
        month = {June},
        }