Sign Language to Speech: the Role of Conversion Gloves in Enhancing Communication

Individuals with speech disabilities often rely on sign language for communication; however, a significant challenge arises when interacting with people who are unfamiliar with it, creating a communication barrier. This study proposes a costeffective solution to address this issue by developing smart gloves that enable speech-impaired individuals to communicate more effectively. The system utilizes gloves embedded with flex and motion sensors to detect various sign language gestures. These sensor readings are processed using an Arduino UNO, which transmits the data to an Android device via a Bluetooth module. Gesture recognition is based on pre-defined patterns corresponding to specific sign language gestures, ensuring efficient processing with minimal latency. While the current prototype focuses on American sign language (ASL), it can be adapted for other sign language variants with appropriate calibration. The system aims to bridge the communication gap by translating users' gestures into text and converting the text into speech, providing a practical and portable solution for real-world scenarios. Challenges related to gesture recognition accuracy, sign language variations, and real-time translation latency are acknowledged, with potential improvements discussed for future work.