International Journal on Science and Technology

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SpeakBraille:Revolutionizing Braille with Speech Synthesis

Author(s) Anitha Vasam, Mukku Nikitha, Dikonda Pavanikalyani
Country India
Abstract In an era of increasing technological advancement, accessibility remains a paramount concern. This project presents a robust and innovative solution for the visually impaired by harnessing the power of computer vision to seamlessly convert Braille into text and voice. The Braille to Text and Voice Conversion System (BTVCS) serves as a transformative tool that bridges the gap between tactile and auditory communication, empowering individuals with visual impairments to access written information independently. The core of the system lies in its ability to accurately recognize Braille characters through image processing and computer vision techniques. Utilizing state-of-the-art machine learning algorithms and deep neural networks, BTVCS interprets Braille patterns with precision, ensuring minimal error rates. The extracted Braille text is then seamlessly converted into natural language text, opening up a world of printed content to the visually impaired. Additionally, BTVCS features a robust text to- speech (TTS) engine that transforms the converted text into high quality, natural-sounding voice output. Users can select from a range of voices and settings to personalize their experience. This dynamic TTS capability extends beyond mere translation; it provides an immersive auditory experience that conveys tone, context, and emotion, making the content more engaging and informative
Keywords Accessibility, Visually Impaired, Braille, Computer Vision, Text-to-Speech (TTS), Machine Learning, Deep Neural Networks, Image Processing, Natural Language Text, Voice Output, Personalization, Convolutional Neural Network
Field Computer
Published In Volume 16, Issue 2, April-June 2025
Published On 2025-05-29
DOI https://doi.org/10.71097/IJSAT.v16.i2.4033
Short DOI https://doi.org/g9mpbn
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