dc.contributor.author |
Ahmed Ifham, Mohamed Abdullah |
|
dc.date.accessioned |
2024-03-21T10:31:35Z |
|
dc.date.available |
2024-03-21T10:31:35Z |
|
dc.date.issued |
2023 |
|
dc.identifier.citation |
Ahmed Ifham, Mohamed Abdullah (2023) Sri Lankan Sign Language to Tamil Audio. BSc. Dissertation, Informatics Institute of Technology |
en_US |
dc.identifier.issn |
2019243 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/1927 |
|
dc.description.abstract |
"The Sri Lankan Sign Language to Tamil Audio Translation System is a groundbreaking project
that aims to bridge the communication gap between the deaf community and the general
population. This project focuses on the development of a robust and user-friendly system that
can efficiently recognize and translate Sri Lankan Sign Language (SLSL) gestures into Tamil
audio. Utilizing advanced computer vision and machine learning techniques, the system is
capable of accurately identifying a wide range of SLSL gestures in real-time. By leveraging
deep learning algorithms and natural language processing, the translation from sign language
to Tamil audio is seamless, enabling smooth communication between the deaf community and
Tamil speakers. Sri Lankan Sign Language to Tamil Audio Translation System is a novel and
valuable contribution to the field of sign language recognition and translation, offering new
possibilities for effective communication between the deaf community and the general
population." |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
|
en_US |
dc.subject |
Sri Lankan Sign Language (SLSL) |
en_US |
dc.subject |
Sign Language to Tamil Audio (SLTA) |
en_US |
dc.subject |
Algorithmic Approach to Sign Language(AASL) |
en_US |
dc.title |
Sri Lankan Sign Language to Tamil Audio |
en_US |
dc.type |
Thesis |
en_US |