Survey on Indian Sign Language Video Generation

Indian Sign Language serves as a primary mode of communication for the hearingimpaired community in India. Over the years, extensive research has been conducted to automate Indian Sign Language gesture generation using various computational approaches. This literature survey provides a comprehensive analysis of existing methods, frameworks, and technologies employed in ISL gesture generation. It reviews state-of-the-art techniques spanning speech-to-text conversion, natural language processing strategies, and gesture synthesis using animation tools such as Hamburg Sign Language Notation System and Signing Gesture Markup Language. The paper also examines deep learning models, including convolutional and recurrent neural networks, for gesture recognition and generation. A detailed comparison of methodologies, datasets, and performance evaluation metrics is presented to identify current trends and limitations in the field. Additionally, the survey discusses key challenges such as data scarcity, linguistic variations, and real-time processing constraints. The study aims to provide insights into the progress made in ISL gesture generation and outlines future directions for developing more robust and user-friendly assistive technologies.