An integrative survey on Indian sign language recognition and translation

Abstract

Hard of hearing (HoH) people commonly use sign languages (SLs) to communicate. They face major impediments in communicating with hearing individuals, mostly because hearing people are unaware of SLs. Therefore, it is important to promote tools that enable communication between users of sign language and users of spoken languages. The study of sign language recognition and translation (SLRT) is a step forward in this direction, as it tries to create a spoken‐language translation of a sign‐language video or vice versa. This study aims to survey the Indian sign language (ISL) interpretation literature and gives pertinent information about ISL recognition and translation (ISLRT). It provides an overview of recent advances in ISLRT, including the use of machine learning based, deep learning based, and gesture‐based techniques. This work also summarizes the development of ISL datasets and dictionaries. It highlights the gaps in the literature and provides recommendations for future research opportunities for ISLRT development.