Indian Sign Language to Text/Speech Translation

Abstract: Indian Sign Language (ISL) is an important visual language used by deaf and hard-of-hearing people in India for communication. However, many people who do not understand sign language face difficulties in communicating with ISL users. In many situations, communication depends on another person who understands sign language, which may not always be available. Therefore, there is a need for a system that can automatically recognize Indian Sign Language gestures and convert them into understandable text and speech.

This research proposes an Indian Sign Language Text/Speech Translation System to make communication between ISL users and non-sign-language users easier and more accessible. The system provides a digital method to capture ISL gestures through a camera, process the input, identify the signs, and convert the recognized gestures into text. The generated text can then be converted into speech using a text-to-speech component. The proposed system can use computer vision, image processing, machine learning or deep learning techniques, and natural language processing for recognizing and translating ISL gestures. The system can support real-time communication and reduce the need for manual interpretation in basic communication situations. It can also provide a foundation for future development of multilingual translation and improved recognition of continuous signs.

Keywords: Indian Sign Language, ISL Translation, Sign Language Recognition, Text Translation, Speech Generation, Computer Vision, Deep Learning, Natural Language Processing.