Interpretation of Sign Language for Physically Challenged Using Machine Learning


Authors : Jayashree G R; Bhargavi Vijendra Sangam; Dr. Girish Attimarad

Volume/Issue : Volume 7 - 2022, Issue 7 - July

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3KqIalB

DOI : https://doi.org/10.5281/zenodo.7021173

Abstract : One of the common ways to communicate with thedeaf people is sign language. Sign language helps them to understand in a very easy manner and it also helps them to communicate. But they should learn sign language in order to communicate. Learning is a huge process and also a difficult task. Initially by using finger spelled task one can learn the sign language. Different signs are assigned to understand different words. The main aim of the project aims at collecting the different datasets and different features are extracted which are very useful and different approaches were used. Also many four folded results have been used to extract many of the information by using many approaches. Also from many of the previous work the results were verified and given many validation sets to train the data.

Keywords : ISL, Sign Language, Machine Learning, Deaf People.

One of the common ways to communicate with thedeaf people is sign language. Sign language helps them to understand in a very easy manner and it also helps them to communicate. But they should learn sign language in order to communicate. Learning is a huge process and also a difficult task. Initially by using finger spelled task one can learn the sign language. Different signs are assigned to understand different words. The main aim of the project aims at collecting the different datasets and different features are extracted which are very useful and different approaches were used. Also many four folded results have been used to extract many of the information by using many approaches. Also from many of the previous work the results were verified and given many validation sets to train the data.

Keywords : ISL, Sign Language, Machine Learning, Deaf People.

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