Paper Contents
Abstract
The Sign Language Teacher is a project developed to make learning sign language simple, interactive, and accessible for everyoneespecially for individuals who are hearing or speech impaired. In todays world, where digital learning has become a norm, the lack of inclusive tools for specially-abled learners became very clear to us. This project was created to bridge that gap using the power of technology.Our system uses computer vision and machine learning to recognize hand gestures through a webcam and teach users the correct signs in real time. It provides immediate feedback to the user, helping them understand and practice sign language accurately and at their own pace. By offering an engaging way to learn, this tool supports both independent learners and educational institutions that want to promote inclusivity in their classrooms.This project is especially valuable for schools, colleges, and training centers that aim to teach sign language to students, educators, or even the general public. It checks whether the user is performing the correct hand sign using gesture detection and gives helpful prompts when a mistake is made. Through this interactive feedback loop, learners can steadily improve their signing skills.Our platform includes a student learning dashboard, categorized modules for different levels of sign learning, and a clean, easy-to-navigate interface. The system is designed to work offline, removing the dependency on internet access and making it suitable for all users regardless of location or connectivity.The main goal of the Sign Language Teacher project is to build a friendly, affordable, and accessible tool that supports inclusive education. It saves time for trainers, empowers learners, and most importantly, takes a step toward breaking communication barriers. This project reflects how technology can be a meaningful ally in creating a world where everyone can learn and communicate freely.
Copyright
Copyright © 2025 Shreya Gupta. This is an open access article distributed under the Creative Commons Attribution License.
