Machine translation from text to sign language: a systematic review

An equal opportunity for all is the basic right of every human being. The deaf society of the world needs to have access to all the information just like hearing people do. For this to happen there should be a mode of direct communication between hearing and deaf people. The need at this time is to automate this communication so as the deaf society is not dependent upon human interpreters. This paper deals with the systematic survey of conventional and state-of-the-art sign language machine translation and sign language generation projects. We used a standard procedure of carrying out a systematic literature review on 148 studies published in 30 reputed journals and 40 premium conferences and workshops. Existing literature about sign language machine translation is broadly classified into three different categories. These categories are further sub-classified into different classifications depending upon the type of machine translation. Studies pertaining to the specified classifications have been presented with their advantages and limitations. Different methods for sign language generation are reported with their benefits and limitations. Manual and automatic evaluation methods used in every study is presented along with their respective performance metrics. We call for increased efforts in presentation of signs to make them an easy and comfortable mode of communication for deaf society. There is also a requirement to improve translation methods and include the contribution of advanced technologies such as deep learning and neural networks to make an optimal translation process between text and sign language.

Automated summary

Equal opportunity is a basic right for everyone, and the deaf society should have access to information just like hearing people do through direct communication. Existing research on sign language machine translation is categorized into three types, discussing their advantages and limitations. Efforts are needed to improve sign presentation and incorporate advanced technologies like deep learning and neural networks for optimal translation between text and sign language.