A comprehensive review on automation of Indian sign language

Abstract

Hearing impaired people uses signs to communicate with others. Just like verbally spoken languages, there is no universal language as every country has its own spoken language so every country has their own dialect of sign language and in India they uses Indian Sign Language (ISL). In the last few years, researchers take interest in the automation of ISL. Some attempts have been made in India and other countries. In this study we try to explore and analyze the work have been made with automation of sign language and gesture recognition. We tried to explore the challenges comes in the real time sign recognition system. This review also includes the progress of standard corpus creation of the ISL.

Recognition of Accessibility Features Using CNN

“…Lots of study has been done on sensor-based approaches like gloves, wires, helmets etc [4][5] [6]. But due to the disadvantage of wear it perpetually is not possible, consequently further work is concentrated on Image based approaches [1]. Some previous work has been done on image based approaches for hand gesture and sign recognition in the last few years [14].There has been various methodologies for gesture recognition like HMM(Hidden markov model) [15], ANN(Artificial neural network) [16], Eigen value based [17], perceptual color based [1][18].In [19] authors proposed gesture apperception algorithm using GMM and HMM.…”

Curvilinear tracing approach for recognition of Kannada sign language

“…Examples of past initiatives and future trends when coping with sign languages are outlined. A temporal dynamics of the generation of sign and the analysis of sign language for ISL were outlined in Verma et al (2015). Bhuyan et al (2006) suggested a sign language recognition using the face and arm interface.…”