Sign Language Recognition, Generation, and Translation

TLDR

Sign language recognition, generation, and translation require expertise across computer vision, graphics, NLP, HCI, linguistics, and Deaf culture, yet research remains siloed. The workshop aimed to answer: what an interdisciplinary view reveals, the biggest challenges, and calls to action for the field. A diverse group of experts convened for a two‑day workshop to address these questions. The workshop produced a review of the state of the art, highlighted overlooked background, identified pressing challenges, and issued a call to action for researchers.

Abstract

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.