Deaf and dumb people's communicate their thoughts
using sign language, which is a visual language. Unlike vocal
communication, sign language makes use of body language and
physical communication to fluidly express a person's thoughts. It
can be used by someone who has trouble communicating or by a
person who can hear but can not speak and also, by normal
people to communicate with hearing disabled people. For deaf
individuals, sign language is a very important factor for their
growth. Our project aims to bridge the gap between these Deaf
people and normal people with the advent of new technologies of
web applications, Machine Learning, and Natural Language
Processing. The main purpose of this project is to build an
interface that accepts Audio/Voice as input and converts them to
corresponding Sign Language for Deaf people. It is
accomplished by incorporating hand forms, orientation, and
movement of the hands, limbs, or body at the same time. The
user interface is divided into two steps, first converting Audio to
Text using speech to text API (webkitSpeechRecognition api) and
secondly, represent the text using Parse Trees and applying the
semantics of Natural Language Processing (NLTK specifically)
for the lexical analysis of Sign Language Grammar. The work
builds upon the rules of ISL(Indian Sign Language) and follows
the ISL rules of Grammar