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@article{191001,
        author = {Bhavesh Rajendra Desale and Tejas Nandkumar Deore and Nayan Nitin Bedse and Darshan Umesh Shitole},
        title = {Real Time Sign Language Translator App},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {5349-5354},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191001},
        abstract = {The Real-Time Sign Language Translator App is a mobile tool designed to bridge the communication gap between sign language users and those who don’t know sign language. The app captures hand movements using the smartphone camera and translates them into spoken language or on-screen text. This feature makes communication smooth and effective. It supports various sign languages, including American Sign Language (ASL), British Sign Language (BSL), and Indian Sign Language (ISL), which helps it reach a broader audience.
The app benefits not only deaf individuals and those with speech challenges but also offers personalized communication support in social, educational, and professional situations. Additionally, it includes features for speech-to-sign translation and customizable gesture mapping, enhancing the user experience and providing personal flexibility.
Built with modern technologies, the app is developed in Kotlin for Android, uses MediaPipe for real-time hand tracking, and employs TensorFlow Lite for gesture recognition optimized for mobile devices. Firebase supports user authentication and real-time data synchronization, ensuring secure and seamless communication, with a focus on accessibility.
The app proves increasingly useful in healthcare, education, and everyday communication. It enables real-time, two-way interactions between people with different abilities and the general public while promoting inclusion by helping users overcome traditional communication barriers.},
        keywords = {Sign Language Translation, Real-Time Gesture Recognition, Mobile Accessibility, Computer Vision, Hand Gesture Detection, MediaPipe, TensorFlow Lite, Android Application, Kotlin Programming, Speech-to-Text Translation, Text-to- Sign Conversion, Assistive Technology, Inclusive Communication, Deaf and Mute Support, Human–Computer Interaction},
        month = {January},
        }