Authors :
V. Jyothi; A. Abilash; Saripalli Shelsi; G. Divij Reddy; R. Sreenidhi Reddy
Volume/Issue :
Volume 8 - 2023, Issue 3 - March
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://bit.ly/3GG7EuP
DOI :
https://doi.org/10.5281/zenodo.7800718
Abstract :
Individuals with hearing and speech
disabilities use sign language as their primary mode of
communication to express their thoughts, ideas, feelings,
and opinions to the rest of the world. They use multiple
complementary channels to convey information as visual
languages. This includes manual characteristics like
hand shape, movement and pose, facial expression, lip
movement, and so on. For someone who has never
learned the language, the sign gestures are frequently
mixed up and confused. Our project focuses on bridging
this gap by recognizing hand gestures and converting
them into readable text and audio speech using machine
learning algorithms, and it also allows written text to be
converted into hand gestures. Sign language recognition
and translation enable us to learn the spatial
representations, underlying language model, and
mapping between sign and spoken language in real time.
Individuals with hearing and speech
disabilities use sign language as their primary mode of
communication to express their thoughts, ideas, feelings,
and opinions to the rest of the world. They use multiple
complementary channels to convey information as visual
languages. This includes manual characteristics like
hand shape, movement and pose, facial expression, lip
movement, and so on. For someone who has never
learned the language, the sign gestures are frequently
mixed up and confused. Our project focuses on bridging
this gap by recognizing hand gestures and converting
them into readable text and audio speech using machine
learning algorithms, and it also allows written text to be
converted into hand gestures. Sign language recognition
and translation enable us to learn the spatial
representations, underlying language model, and
mapping between sign and spoken language in real time.
