Towards Seamless Communication for Sign Language Support: Architecture, Algorithms, and Optimization
摘要
This study delves into the practical implementations of Computer Vision and Machine Learning within real-world contexts, specifically addressing the facilitation of communication between individuals with speech impairments and those without. The investigation focuses on deploying a learning model integrated with Computer Vision, designed to assimilate input data and generate user-friendly outputs. The refined model is subsequently adapted for seamless integration into over-the-counter transactions, streamlining consumer communication processes. A proposed solution, the Sign Assistance Ready App (SARA), is introduced in this report to address the identified communication gap. Throughout the ensuing sections, the application will be denoted as SARA for brevity and clarity.