TY - GEN
T1 - AI-Driven Sign Language Interpretation for Nigerian Children at Home
AU - Nwogu, Ifeoma
AU - Peiris, Roshan
AU - Dantu, Karthik
AU - Gamta, Ruchi
AU - Asonye, Emma
N1 - Publisher Copyright:
© 2023 International Joint Conferences on Artificial Intelligence. All rights reserved.
PY - 2023
Y1 - 2023
N2 - 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 school often readily and effectively communicate 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 which can promote lifelong learning opportunities for the students outside of the school environment.
AB - 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 school often readily and effectively communicate 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 which can promote lifelong learning opportunities for the students outside of the school environment.
UR - https://www.scopus.com/pages/publications/85170388118
U2 - 10.24963/ijcai.2023/710
DO - 10.24963/ijcai.2023/710
M3 - Conference contribution
AN - SCOPUS:85170388118
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 6395
EP - 6404
BT - Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
A2 - Elkind, Edith
PB - International Joint Conferences on Artificial Intelligence
T2 - 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
Y2 - 19 August 2023 through 25 August 2023
ER -