  The people in the world who are hearing impaired face many obstacles in
communication and require an interpreter to comprehend what a person is saying.
There has been constant scientific research and the existing models lack the
ability to make accurate predictions. So we propose a deep learning model
trained on ASL i.e. American Sign Language which will take actions in the form
of ASL as input and translate it into text. To achieve the translation a
Convolution Neural Network model and a transfer learning model based on the
VGG16 architecture are used. There has been an improvement in accuracy from 94%
of CNN to 98.7% of Transfer Learning, an improvement of 5%. An application with
the deep learning model integrated has also been built.
