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# ceng-407-408-2023-2024-SignLang2Utterance

Sign Language To Speech

Project Description

The primary purpose of the "Sign Language to Speech" project is to develop an innovative and inclusive communication system that translates sign language gestures into spoken language. This initiative aims to bridge the communication gap between individuals who are deaf or hard of hearing and those who do not understand sign language. By leveraging advanced computer vision and machine learning techniques, the project seeks to:

Enable Effective Communication: Provide a real-time translation solution that allows seamless interaction between sign language users and the general public, fostering inclusivity in various social, educational, and professional settings.

Empower Individuals with Hearing Impairments: Enhance the independence and social engagement of deaf and hard-of-hearing individuals by facilitating their communication with a wider audience, beyond those familiar with sign language.

Innovate Accessibility Technologies: Push the boundaries of accessibility technology by developing a sophisticated system that accurately recognizes, interprets, and translates sign language gestures through a combination of gesture recognition, hand tracking, and speech synthesis techniques.

Create a User-Friendly Interface: Ensure that the technology is accessible and easy to use for all, including those with hearing impairments, by designing an intuitive user interface that simplifies interaction with the system.

Ultimately, the project aspires to create a world where communication barriers for individuals with hearing impairments are significantly reduced, promoting greater inclusion, understanding, and equality in everyday interactions.

Documents

Project Workplan

SRS

Literature Review

SDD

Project Report

Project Website

Team Members

Team Members Student Numbers
Ethem Ali Ayral 201911013
Doğukan Kaska 201911203
Bora Çınar 201911021
Bartu Aslan 202011008
Ali Alper Yaman 201911070

Advisor

Prof. Dr. Hayri SEVER