Machine learning based sign language recognition: a review and its research frontier

摘要

In the recent past, research in the field of automatic sign language recognition using machine learning methods have demonstrated remarkable success and made momentous progression. This research article investigates the impact of machine learning in the state of the art literature on sign language recognition and classification. It highlights the issues faced by the present recognition system for which the research frontier on sign language recognition intends the solutions. In this article, around 240 different approaches have been compared that explore sign language recognition for recognizing multilingual signs. The research done by various authors is also studied, and some of the important research articles are also discussed in this article. Based on the inferences from these approaches, this article discussed how machine learning methods could benefit the field of automatic sign language recognition and the potential gaps that machine learning approaches need to address for the real-time sign language recognition.