Recognition of Indian Sign Language using Machine Learning Algorithms
Mitali Potnis, Divya Raul, Madhura Inamdar · 2021
Auditory perception enables an individual to sense sound vibrations caused due to the variations in pressure present. In accordance with WHO, 6.3% of the Indian population suffers from hearing disability. People that suffer from hearing impairment communicate using hand gestures. Unfortunately, the vast majority of the people in India are not aware of the semantics of these gestures. To bridge the gap between the people suffering from hearing disabilities and those who are not, we have proposed an Indian sign language Recognition system using machine learning algorithm techniques. Our method utilizes several images of people demonstrating the alphabets in Indian Sign Language. These images are pre-processed, and further, we utilize these obtained images for training and testing our Machine Learning Algorithms. Out of all the six machine learning algorithms that we used, Random Forest Machine Learning Algorithm gave the highest accuracy of 98.44%.