AfriSign: Machine Translation for African Sign Languages

Shester Gueuwou, Kate Takyi, Mathias Müller, Marco Stanley Nyarko, Richard Adade, Rose-Mary Owusuaa Mensah Gyening

Keywords: Machine Translation, Sign Languages, Low Resource Languages

TL;DR: End-To-End Machine Translation For Six African Sign Languages

Abstract: Sign language translation is an active area of research with the main goal of bridging the communication gap between deaf and hearing individuals. In Natural Language Processing (NLP), there is a growing interest in this task, leading to new datasets and research on translation approaches. But while there has been significant progress for sign languages from high-income countries, minimal research has been conducted on African sign language translation. In this paper, we curate a novel dataset of African sign languages, with a focus on machine translation as the main application. The dataset contains English Bible verses and videos with translations into six different African sign languages. Using this dataset, we report experiments on African sign language machine translation, including baseline Transformer systems, multilingual training and cross-lingual transfer learning.