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@article{202443,
        author = {Lalana and Prerana Hebsur and Maruthi Reddy B M and Mahammed Kaif H and Mithun B N and Krushitha Shetty},
        title = {Advancements in OCR and TTS Systems: A Review of Technologies for Accessibility},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {8577-8582},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=202443},
        abstract = {Optical Character Recognition (OCR) and Text-To-Speech (TTS) are vital technologies that allow machines to read and articulate written content. OCR retrieves text from images, scanned papers, and photographs, whereas TTS translates this text into natural, human-like voice. When combined, these technologies form powerful OCR-TTS systems that improve accessibility for individuals with visual disabilities by delivering real-time audio output from both printed and digital materials. In addition to accessibility, their integration benefits various sectors. In education, OCR-TTS tools convert textbooks and educational materials into audio format, promoting inclusivity for students with reading difficulties. In the logistics and supply chain sectors, they optimize processes by reading labels, invoices, and shipping papers. For language learners, these systems provide auditory feedback that improves pronunciation and understanding. In smart cities, they can vocalize signs, timetables, and announcements for the public. This review emphasizes developments in segmentation, language modeling, Transformer-based OCR, and neural TTS, highlighting their potential for automation, inclusivity, and improved user interaction.},
        keywords = {Embedded system, OCR, TTS, pytesseract, gtts, trOCR.},
        month = {May},
        }