Kaushal Kishore Rao Mangalore - Department of MCA, School of Computer Science and IT, Jain (deemed-to-be) University, Bengaluru, India.
Nikhitha Pradeep - Department of MCA, School of Computer Science and IT, Jain (deemed-to-be) University, Bengaluru, India.
Bhawesh Rajpal - Department of MCA, School of Computer Science and IT, Jain (deemed-to-be) University, Bengaluru, India.
Nitin Prasad - Department of MCA, School of Computer Science and IT, Jain (deemed-to-be) University, Bengaluru, India.
Ravi Shastri - Department of MCA, School of Computer Science and IT, Jain (deemed-to-be) University, Bengaluru, India.

The move to standardize Indian Sign Language has created an opportunity for researchers to focus on solving local problems, to increase its reach. In this paper, a survey and assessment of the techniques applied to the recognition and conversion of Indian Sign Language are performed. An overview of the techniques used in sign language recognition for Indian Sign Language is provided to understand the status of research in this field. Following this, a comparison of techniques aimed at rendering a more detailed picture of the research results is presented. The challenges faced by researchers, the limitations of current techniques, and the need for improved research in this area are highlighted. With the intent of spurring more in-depth research, key areas within the approaches and techniques in need of improvement are summarized.

Indian Sign Language, Sign Language Recognition, Gesture recognition, convolutional neural network, Multilayer Perceptron, Neuro-fuzzy system