SURVEY PAPER ON REAL TIME SIGN LANGUAGE INTERPRETER

Abstract

Deaf and Dumb people use sign language to communicate. There are various sign recognition techniques that produce output in the form of words or identified signs. The suggested method focuses on Sign Language Interpretation in correct sentences .In addition to sign identification several NLP (Natural Language Processing) techniques are applied .Input is given as video of sign language followed by framing and segmentation on video. Deaf people get isolated as result of this. However, if an android application can be developed to convert sign language into written and audio format, the gap between normal people and the deaf community can be narrowed. The HAAR CASCADE classifier is used to identify signs. The continuous words for each sign are sent as input to the POS (Part of Speech) tagging module after sign recognition. It is utilized a word net POS tagger with its own word net dictionary. Finally, the sentence is framed using the LALR Parser. In this approach the suggested sign language Interpreter model produces intelligible sentence. This sentence is again converted into audio using gTTS API .We will be developing an android application which will scan the sign languages and interpret it into specific sentence and audio using which a normal person can understand the language of Deaf and Dumb People.