Team Members:
- Ziad Thabe
- Amr Tarek
- Karim Azmi
- Youssef Samy
Supervisors:
- Dr. Mai El-Shehaly
- Dr. Ghada Khoreba
Project Description:
Lip-reading is to understand what someone is saying by watching the movements of their mouth. Lipreading plays a vital role in human communication and speech understanding however, it is a difficult task to be done by humans. Thus, the main goal of this project is to develop a deep learning approach for the real-time detection of spoken words. The training of a deep-layered CNN and RNN is being used to convert lips movement to written words.
Achievements:
- Published a paper entitled “Lipreading Using a Comparative Machine Learning Approach” in the 1st International Workshop on Deep and Representation Learning” IWDRL Conference. https://ieeexplore.ieee.org/document/8358210/
- First Place Winner of the “Three Minutes Thesis” Competition that took place during AUC Tech Summit 2018.
- Winning the 2nd place award at “The Emirates NBD S.A.E Future Intelligence Program 2017”.
Project’s Video:
Proposal Document:
SRS Document:
software-requirement-specification
SDD Document:
software-design-document-Lip-Drive
Demo: