Paper Title
ASL Recognition and Translation Using Data Gloves
Abstract
Sign Language plays a vital means of communica- tion for the Dumb community However, the challenge arises
when individuals proficient in sign language try to connect with those unfamiliar with it. The existing system involves the
Recognition of sign language. Future enhancements could focus on refining the accuracy and speed of gesture Recognition,
incorporating machine learning, and exploring ergonomic glove designs for user comfort. This project aims to develop an
innovative sign language Recogniser and translator tailored to the dumb community. The system employs a smart glove
that captures intricate hand movements of both hands. The data (sign values) is recorded using an integrated control unit
consisting of Arduino, flex sensors, MPU-6050, RF module, etc. After this, it is transmitted to an android application
consisting of two algorithms, the Random Forest Algorithm for Recognising the numeric data into equivalent sign gestures
and the transformer-based translator that is responsible for the conversion of Recognised sign-language text into English text.
The objective is to seamlessly integrate Recognition and translator functionalities, offering a solution that adds
functionalities and a user interface, creating a tool for individuals using sign language.
Keywords - ASL, Data glove, Arduino Uno, Flex Sen- sors,touch sensors, MPU-6050, RF module, Bluetooth module,
Android Application, Random Forest, Gramformer
Author - Nupur V. Chavan, Raj D. Telgote, Pallavi V. Gaikwad, Satish S. Kumbhar
Published : Volume-11,Issue-6 ( Jun, 2024 )
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Published on 2024-09-26 |
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