Survey on Sign Language Identification Using Deep Learning
Author(s):
Nadeem Gulam, Neha Pandey, Medha R, Rakshith Vk, Vasudeva G
Keywords:
ConvolutionalNeural Networks.
Abstract
Hearing and speech impairment is one of the most challenging problems faced by people with disabilities. The proposed system provides a platform which helps people with speech disability communicate with the world. Sign language is the mode of communication for speech deprived people and other people cannot interpret their language effectively and this causes a hindrance to them. And as a consequence, people with disabilities who are a minority in the community cannot perform even basic tasks. So, the idea proposed is a system which converts Sign Language (SL) to text and speech output. This is implemented using convolutional neural networks (CNN) to extract efficient hand features to identify the hand gestures according to Sign Language. Hence, this model helps in recognizing the hand gestures of people with disabilities and converting them to text and speech to allow them to communicate effectively.
Article Details
Unique Paper ID: 158225

Publication Volume & Issue: Volume 9, Issue 9

Page(s): 170 - 173
Article Preview & Download


Share This Article

Join our RMS

Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Call For Paper

Volume 10 Issue 10

Last Date for paper submitting for March Issue is 25 June 2024

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews