Publication Date: 2023/07/15
Abstract: Lack of speech is a recognized disability that significantly impacts communication abilities. Individuals with this disability employ various methods to interact with others, with sign language being one of the most prevalent and effective forms of communication. Sign language allows deaf and hard of hearing individuals to convey information within their community and beyond. This study focuses on the electronic recognition of sign language, encompassing everything from sign production to text or speech output. The recognition process involves distinguishing between fixed and flexible touch gestures, and this study outlines the steps undertaken. These steps include data acquisition, preprocessing, data augmentation, feature extraction, segmentation, and evaluation of the obtained results. Additionally, this study provides recommendations for future research in this area, serving as a guide for further advancements in sign language recognition.
Keywords: Mediapipe, Sign language recognition [SLR], CNN, Computer Interaction with Humans.
DOI: https://doi.org/10.5281/zenodo.8149817
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23JUN2423.pdf
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