VoiceofHands : a sign language recognition app

Abstract

This report presents the development of VoiceofHands, a sign language recognition application designed to detect and interpret hand gestures used in sign language, addressing the need for improved accessibility tools for deaf and hard-of-hearing communities. Leveraging deep learning techniques and the YOLO framework, the system provides a user-friendly interface with robust performance across a variety of sign language gestures. Motivated by the limitations of existing sign language recognition systems, particularly in handling complex hand movements and diverse gestures, VoiceofHands aims to provide accurate and reliable gesture recognition with minimal user intervention. The application enables real-time gesture recognition and translation using advanced machine learning algorithms to interpret sign language and provide instant translations and descriptions through an intuitive interface. It is designed to support both fluent signers and learners while prioritizing user privacy and data security. The proposed system has potential applications in education, healthcare, and public services, where it can help reduce communication barriers and promote inclusivity. Continuous refinement based on user feedback and expert collaboration can further improve the systems accuracy and usability. VoiceofHands represents a step toward more accessible communication by leveraging artificial intelligence to bridge gaps between sign language users and the wider community.