Translation of Gesture-Based Static Sign Language to Text and Speech

As human beings, most of us convey our thoughts by speech and facial expressions, but according to the latest survey conducted, it was found that roughly 1% of the population in India is deaf and mute. These people communicate with others using hand gestures and facial expressions. However, most peo...

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Bibliographic Details
Published in:Journal of physics. Conference series 2021-07, Vol.1964 (6), p.62074
Main Authors: Gauni, Sabitha, Bastia, Ankit, Sohan Kumar, B, Soni, Prakhar, Pydi, Vineeth
Format: Article
Language:English
Subjects:
Background Isolation
Convolutional Neural Network
Gesture Recognition
Image Thresholding
Pre-Processing
Sign language
Speech
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Summary:As human beings, most of us convey our thoughts by speech and facial expressions, but according to the latest survey conducted, it was found that roughly 1% of the population in India is deaf and mute. These people communicate with others using hand gestures and facial expressions. However, most people find it difficult to understand gestures. To eliminate this gap, we develop static gesture classification based on sign language standards and then converting to text and speech of a given local dialect.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1964/6/062074