Gesture to Speech: A Wearable Solution for Sign Language Translation
A Balamanikandan, R Bindu Madhavi, Pudi Abhiram Reddy, Pinjari Ameer Sohel, Pamala Vijay Kumar, Nagarajan Ashokkumar · 2024
This paper introduces a groundbreaking wearable device designed to address communication challenges faced by the global mute community. The device utilizes embedded flex sensors strategically placed on a glove to capture intricate sign language gestures. An embedded system, featuring a microcontroller (Arduino), processes these gestures through a sophisticated translation algorithm, converting them into both textual and speech output. The seamless integration of Bluetooth technology enables real-time wireless communication with external devices, such as smartphones or tablets. The device's versatile design ensures comfort and unobtrusiveness, making it suitable for various social, educational, and professional settings. Additionally, a rechargeable battery and efficient power management contribute to prolonged and sustainable usage. The embedded system's role is pivotal, acting as the cognitive hub that interprets and translates sign language gestures, fostering inclusivity and breaking down communication barriers. The translation algorithm, backed by machine learning techniques, enhances accuracy, making the device a reliable and practical solution. The optional inclusion of Text-to-Speech software further enriches the user experience, offering a comprehensive communication tool for the mute community. This paper discusses the device's technological architecture, design considerations, and real-world applications, emphasizing its transformative impact on global inclusivity. The research explores the potential for widespread adoption and its contribution to creating a more accessible and cohesive world.