Chakrabarty, AmitabhaChowdhury, Ariq SadiqBakhtiar, Rafid BinChakraborty, AritraForaejy, Aowfi Adon2026-08-092026-08-0920262026-01ID 22101817ID 22101856ID 22101892ID 22101095https://hdl.handle.net/10361/28839This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2026.Cataloged from PDF version of thesis.Includes bibliographical references (pages 70-73).Braille is an essential mode of communication for visually impaired individuals, enabling them to read and understand contexts through a tactile system of raised dots. However, certain regions worldwide, especially Bangladesh, have limited access to digital solutions for Braille conversion, which poses a challenge for those individuals. This thesis presents a method for converting Braille Characters to Bangla Voice through a deep-learning based system and thus enhancing accessibility for visually impaired individuals as well as general individuals who cannot understand Braille. In this research we have addressed the scarcity of high volume labeled data consisting of more than 10000 high-resolution labeled data with approximately 1 million labeled braille instances by strictly maintaining Library of Congress spatial standards. This research simulataniously performs two different architecture one being a multi-stage segmentation-classification and other one being YOLO based unified architecture. The unified architecture vastly outperforms the traditional method by achieving Mean Average Precision (mAP@50) of 98.5 percent in character extraction. The recognized text is then converted into natural-sounding Bangla speech using a TTS engine. This system is evaluated through accuracy, processing speed, and friendly user experience, demonstrating its potential to bridge the communication gap for the visually impaired in Bangla-speaking communities.82 pagesen-USAttribution-NonCommercial-NoDerivatives 4.0 InternationalBRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.http://creativecommons.org/licenses/by-nc-nd/4.0/Deep learningConvolutional neural networksVoice conversionBengali languageCharacter classificationLarge language modelsVGG16ResNet50MobileNetV3Braille charactersBraille conversionText-to-speechBraille segmentationImage processingNatural language processing (Computer science).Pattern recognition systems.Speech processing systems.Optical pattern recognition.Speech synthesis.Braille.Neural networks (Computer science).Thesis