Open AccessSign Language Recognition using Deep Learning
Author(s) -
Dhruv Sood
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40627
Subject(s) - sign language , gesture , american sign language , computer science , sign (mathematics) , gesture recognition , transfer of learning , speech recognition , natural (archaeology) , language acquisition , natural language processing , artificial intelligence , linguistics , psychology , mathematics education , history , mathematical analysis , philosophy , mathematics , archaeology
Millions of people with speech and hearing impairments communicate with sign languages every day. For hearingimpaired people, gesture recognition is a natural way of communicating, much like voice recognition is for most people. In this study, we look at the issue of translating/converting sign language to text and propose a better solution based on machine learning techniques. We want to establish a system that hearing-impaired people may utilise in their everyday lives to promote communication and collaboration between hearing-impaired people and people who aren't trained in American Sign Language (ASL). To develop a deep learning model for the ASL dataset, we'll use a technique called Transfer Learning in combination with Data Augmentation. Keywords: Sign language, machine leaning, Transfer learning, ASL, Inception v3