AI-Driven Sign Language Interpretation for Nigerian Children at Home

AI-Driven Sign Language Interpretation for Nigerian Children at Home

Ifeoma Nwogu, Roshan Peiris, Karthik Dantu, Ruchi Gamta, Emma Asonye

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence
AI for Good - Projects. Pages 6395-6404. https://doi.org/10.24963/ijcai.2023/710

As many as three million school age children between the ages of 5 and 14 years, live with severe to profound hearing loss in Nigeria. Many of these Deaf or Hard of Hearing (DHH) children developed their hearing loss later in life, non-congenitally, hence their parents are hearing. While their teachers in the Deaf schools they attend can often communicate effectively with them in "dialects" of American Sign Language (ASL), the unofficial sign lingua franca in Nigeria, communication at home with other family members is challenging and sometimes non-existent. This results in adverse social consequences including stigmatization, for the students. With the recent successes of AI in natural language understanding, the goal of automated sign language understanding is becoming more realistic using neural deep learning technologies. To this effect, the proposed project aims at co-designing and developing an ongoing AI-driven two-way sign language interpretation tool that can be deployed in homes, to improve language accessibility and communication between the DHH students and other family members. This ensures inclusive and equitable social interactions and can promote lifelong learning opportunities for them outside of the school environment.
Keywords:
AI for Good - Projects: Humans and AI
AI for Good - Projects: Natural Language Processing
AI for Good - Projects: Computer Vision