ShopRecog: Mobile application for shop recognition with text to speech
This report documents the development and implementation of the "ShopRecog" mobile application, designed to address the unique needs of visually impaired individuals by leveraging advanced technologies such as machine learning, text recognition, and API integrations. The application provid...
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| Format: | Final Year Project / Dissertation / Thesis |
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2024
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| Online Access: | http://eprints.utar.edu.my/6643/ http://eprints.utar.edu.my/6643/1/fyp_CS_2024_KZY.pdf |
| Summary: | This report documents the development and implementation of the "ShopRecog" mobile application, designed to address the unique needs of visually impaired individuals by leveraging advanced technologies such as machine learning, text recognition, and API integrations. The application provides real-time shop recognition, interactive speech-to-text functionality, comprehensive shop information retrieval, AI-generated summaries, and navigation assistance, all tailored for a seamless and user-friendly experience. Through rigorous testing, performance evaluation, and user feedback, the application demonstrates its effectiveness in enhancing independence, information access, and navigation support for visually impaired users. The report concludes with recommendations for continuous improvement, localization, adherence to accessibility standards, user feedback integration, and collaboration for further impact and innovation in assistive technologies. |
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