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