Abstract
Sign language is the main source of communication for the deaf-mute people. These people go through many kinds of problems whilst communicating in person or through any other devices. To overcome this communication barrier, they need an interpreter which converts the sign language into text. In some situations, these impaired people may be unknown with sign language. Thus, necessity of sign interpreter is unpreventable. Developing this kind of interpreter needs a wide range of knowledge in fields such as deep learning, image processing, and convolution networking. The crucial point of this analysis is to know whether recognizing the gesture can succeed in assisting the self-learners in learning the sign language. This ideology can avoid their quarantine from the rest of the society notably. Results from this literature review could help in development of an efficient sign interpreter which helps for the communication between non-signer and a signer.
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Srikanteswara, R., Niveditha, C.B., Sindhu Sai, A., Reddy, R.K., Akshayanjali, S.A. (2022). Sign Language Interpreter. In: Pandian, A.P., Fernando, X., Haoxiang, W. (eds) Computer Networks, Big Data and IoT. Lecture Notes on Data Engineering and Communications Technologies, vol 117. Springer, Singapore. https://doi.org/10.1007/978-981-19-0898-9_7
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DOI: https://doi.org/10.1007/978-981-19-0898-9_7
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