Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective
It highlights the need for integrated approaches in sign language recognition, generation, and translation to benefit Deaf communities, but is incremental as it synthesizes existing knowledge rather than presenting new methods.
This paper addresses the fragmented research in sign language processing by conducting an interdisciplinary workshop to review the state-of-the-art, identify key challenges, and propose calls to action for the field.
Developing successful sign language recognition, generation, and translation systems requires expertise in a wide range of fields, including computer vision, computer graphics, natural language processing, human-computer interaction, linguistics, and Deaf culture. Despite the need for deep interdisciplinary knowledge, existing research occurs in separate disciplinary silos, and tackles separate portions of the sign language processing pipeline. This leads to three key questions: 1) What does an interdisciplinary view of the current landscape reveal? 2) What are the biggest challenges facing the field? and 3) What are the calls to action for people working in the field? To help answer these questions, we brought together a diverse group of experts for a two-day workshop. This paper presents the results of that interdisciplinary workshop, providing key background that is often overlooked by computer scientists, a review of the state-of-the-art, a set of pressing challenges, and a call to action for the research community.