American Sign Language Recognition Using CNN
Keywords:
Convolutional Neural Network (CNN), Spatio-temporal features, Vision based techniquesAbstract
Speech impairment is a disability that affects person's ability to communicate using speech and by hearing. Non signers use other medium of communication such as sign language. Although sign language is ubiquitous, non-signers found it challenging to communicate with signers. This paper discusses some of the methods (SVM, KNN, Logistic regression and CNN) that can be used to implement a method to help make the communication of a non-signer with a signer much easier. At the end of the discussion, it was found that convolutional neural network is the most effective technique among the other methods. The main focus is to create a vision-based application which offers sign language recognition to text thereby enabling dynamic communication between them at real time.
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Copyright (c) 2020 U. Hari Priya, S. Krishna Prasad, Meba Meria Jacob, R. Radhu Krishna, P. R. Vinod
This work is licensed under a Creative Commons Attribution 4.0 International License.