Voice-controlled browser extension using machine learning for enhanced accessibility

Abstract

This project presents a voice-controlled browser extension designed to enhance web accessibility and convenience through natural language voice commands. Targeting users with motor and visual impairments, as well as those seeking hands-free multitasking, the system integrates the Web Speech API for real-time speech recognition and TensorFlow.js for machine learning-based command interpretation, complemented by browser automation techniques. Its user-centered design incorporates intuitive voice commands and feedback mechanisms, ensuring the extension is approachable for non-technical users. The modular and scalable architecture facilitates easy updates and supports potential expansions, such as broader command sets, multi-language capabilities, and additional accessibility features like text summarization or translation. Key contributions include improved accessibility for users with disabilities, seamless support for multitasking, and the practical integration of interdisciplinary technologies. By successfully executing a range of browser commands, this work advances human-computer interaction and underscores the transformative potential of voice-driven interfaces in creating more inclusive digital environments.