An end-to-end working prototype that detects sign language meanings in images/videos and generate equivalent, realistic voice of words communicated by the sign language, in real-time.
Steven Kolawole
CS Undergrad @FUNAAB, Nigeria
Previously @#3
Next steps @#3
Contact:
kolawolesteven99@gmail.com
Sign-to-Speech Model for Sign Language Understanding using Object Detection:
A Case Study of Nigerian Sign Language
Steven Kolawole
September 22, 2021
#4
Synopsis
To develop a lightweight sign-to-speech machine learning application that works in real-time to reduce the communication barrier between the hearing impaired community and the larger society with a focus on sub-Saharan Africa, which is the region with most cases of hearing disabilities.
Dataset
Creating low-resource dataset with Nigerian Sign Language as a case study;
Dataset
Creating low-resource dataset with Nigerian Sign Language as a case study;
Dataset
Image Annotation using LabelImg;
Architecture
Evaluation
Evaluation
Evaluation
Challenges
Next steps
Contact:
kolawolesteven99@gmail.com