THE REAL TIME SIGN LANGUAGE DETECTION USING ML
International Research Journal of Modernization in Engineering Technology and Science · 2023
A machine learning model is trained to recognise sign language movements using a large dataset of labelled sign language examples.To capture the varied qualities of different sign motions, several feature extraction approaches such as form descriptors, hand motion vectors, and skeletal tracking are used.These attributes are then given into a real-time classification system, such as a SVM or a CNN, which properly classifies the observed motions.The efficiency of real-time sign language detecting systems is crucial.To ensure real-time speed, optimisation techniques such as parallelization and hardware acceleration (e.g., GPU use) are used.Furthermore, the system may be configured to run on mobile devices or embedded systems, increasing accessibility and usability.