Signs to Speech

Authors

Presenter(s)

Yashesh Dinesh Bharti

Comments

This project reflects research conducted as part of a course project designed to give students experience in the research process. Course: CPS 599

Files

Description

There are softwares which translate from any language to any language, however, the promise of the futuristic sign language decoders have always been far away from being a day to day reality,Proposing a Neural Network based Sign language to speech translator which purports to translate sign language in real-time to text or speech as the user gestures. For people in the Deaf community, this tool could come in handy as it will not demand any extra hardware and use a camera (Like the ones present on the phone) to detect the pose and gestures.

Publication Date

4-22-2020

Project Designation

Course Project

Primary Advisor

Van Tam Nguyen

Primary Advisor's Department

Computer Science

Keywords

Stander Symposium project, College of Arts and Sciences

United Nations Sustainable Development Goals

Sustainable Cities and Communities

Recommended Citation

"Signs to Speech" (2020). Stander Symposium Projects. 1796.
https://ecommons.udayton.edu/stander_posters/1796