Abstract
AbstractSign language (SL) is an alternative way of communication for hearing/speech impaired people. SL varies from country to country. Thus, different SLs came into existence such as American Sign Language (ASL), Chinese Sign Language (CSL), British Sign Language (BSL) and so on. In India, people use Indian Sign Language (ISL) as an alternative communication medium. Approximately, 2.7 million Indian people are deaf/dumb, out of which 98% population uses ISL for communication. But human interpreters are not available or affordable for identifying ISL. Thus, researchers are focussing on Sign Language Recognition System (SLRS) for the identification of ISL. But designing an SLRS for ISL is very difficult in comparison with other SL. ISL is very complex as it consists of single- and double-handed gesture and has an extensive vocabulary with similar gestures. This paper aims to provide a thorough study of ISL, its syntax/vocabulary and different trending techniques for designing an ISL recognition system. This paper also discusses various feature extraction techniques, classification methods used in ISL recognition and points out some challenges researchers face while developing an ISL recognition system.KeywordsIntelligent systemMachine learningCNNSign languageISLExpert systemChallengesSLRSISL syntaxInterpretersTrending techniques
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