Action Detection for Sign Language using Machine Learning Algorithms

This study focuses on overcoming communication challenges for individuals with hearing impairments by exploring automated recognition of sign language signals. People with hearing impairments can communicate better and engage with the community more effectively when automated sign language signals a...

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Bibliographic Details
Main Authors: Modi, Disha, Selvarani, C R, Vaidya, Adithya S, Venkatachalam, Chandrasekar, Neerugatti, Vikram, Mahesh, T R
Format: Conference Proceeding
Language:English
Subjects:
Auditory system
Deep learning
effective interpretation
Image analysis
Long short term memory
LSTM
Mobile applications
Prediction algorithms
Real-time systems
Sign language
Symbols
video analysis
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Summary:This study focuses on overcoming communication challenges for individuals with hearing impairments by exploring automated recognition of sign language signals. People with hearing impairments can communicate better and engage with the community more effectively when automated sign language signals are recognised. Utilizing deep learning, particularly Long short-term memory (LSTM) algorithms, the system analyses images or videos of manual sign signals captured by a camera, predicting corresponding sign language expressions. This innovative approach, leveraging temporal dependencies in gestures, aims to efficiently reduce the communication gap, providing an advanced and effective solution for sign language interpretation.
ISSN:2473-5655
DOI:10.1109/CSNT60213.2024.10545948