Open AccessTHAI SIGN LANGUAGE TO ENGLISH TRANSLATION USING VARIABLE HIDDEN NEURON ANN - A CASE STUDY
Author(s) -
M N Sowjanya,
S N Thimmaraju
Publication year - 2021
Publication title -
international journal of research - granthaalayah
Language(s) - English
Resource type - Journals
eISSN - 2394-3629
pISSN - 2350-0530
DOI - 10.29121/granthaalayah.v9.i9.2021.4281
Subject(s) - sign (mathematics) , sign language , syllable , linguistics , computer science , government (linguistics) , set (abstract data type) , american sign language , artificial intelligence , natural language processing , speech recognition , mathematics , programming language , philosophy , mathematical analysis
Sign language translation has been a major challenge in all walks of life. The current society has been more accepting of the specially abled and the government has been actively making policy changes to accommodate and assimilate the specially abled into the society. Every country has made a conscious effort to develop its own syllable set in its native language even though globally used language is American Sign Language (ASL). In this paper a method proposed by the authors for ASL is applied on Thai Sign Language and the working of the ANN model is explored.