Sign Language Detection with Voice Command

The process of recognizing and deciphering the movements, gestures, and symbols used in sign language is known as sign language detection. This device facilitates communication between those who are deaf or hard of hearing and those who are not familiar with sign language. It functions by examining video footage and identifying important elements such as body language, face expressions, and hand and arm movements. Using machine learning, particularly convolutional neural networks, signs and gestures may be classified with 95–98% accuracy. Its utility can be increased by including record and history tabs, and the dataset can be modified to accommodate various sign languages. This technology has the potential to significantly enhance communication and education for those who are hard of hearing

Authors

Publication Details

Journal
International Journal of Advanced Research in Science Communication and Technology
Published
2024-10-24
DOI
https://doi.org/10.48175/ijarsct-19952
Citations
1
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.37
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Sign Language Detection with Voice Command

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Sign Language Detection with Voice Command

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article en
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Abstract

The process of recognizing and deciphering the movements, gestures, and symbols used in sign language is known as sign language detection. This device facilitates communication between those who are deaf or hard of hearing and those who are not familiar with sign language. It functions by examining video footage and identifying important elements such as body language, face expressions, and hand and arm movements. Using machine learning, particularly convolutional neural networks, signs and gestures may be classified with 95–98% accuracy. Its utility can be increased by including record and history tabs, and the dataset can be modified to accommodate various sign languages. This technology has the potential to significantly enhance communication and education for those who are hard of hearing

International Journal of Advanced Research in Science Communication and Technology
Quality Education
Openalex Percentile: Top 38%
Hand Gesture Recognition Systems
0.37
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