• Ankita Wadhawan

Sign language is an important method of communication among the deaf and hearing impaired people around the world. In India, there are 19% of the disabled persons having hearing disability and it is necessary to educate them so that they can come forward in the society and withstand with the other persons. Education is important for every human that nowadays is explicitly stated in various international documents of many countries. However, the education of deaf children has not received enough importance in India so far. This caused a major lack of infrastructure and support to the cause. Children in villages and remote areas of India that are hearing impaired have very less chance of getting quality education. The use of sign language is very rare and mostly ignored. The times are now changing and Indian Sign Language is slowly getting importance. As Indian education is mostly based on oral skills and it conflicts with the education of children who can’t speak and hear, due to which the growth in education sector for hearing impaired children in India has hampered. However, a change in the mentality and attitude is gradually becoming apparent and Indian Sign Language recognition systems appears as a vital resource of hearing impaired education in many parts of the country. In this paper, an Indian sign language recognition system used for educating students is proposed. The objective of this study is to understand the experiences of hearing impaired students who attended deaf schools and identify with the deaf culture. This paper presents the current status of education of hearing impaired students in India. It also presents the major challenges or hindrances that come forward in the education of hearing impaired and how the proposed system of sign language recognition helps to address these challenges. In the proposed system, the depth data collected using Microsoft Kinect has been used to recognize forty static signs of Indian Sign Language (ISL). All the signs are recorded by using Kinect Studio and Visual Gesture Builder (VGB) has been used for analyzing and tagging of the recorded clips. The recorded clips are analyzed using depth, skeletal and IR data at various angles and positions. The system is trained with 80 samples collected for each of the forty static signs by using AdaBoost machine learning approach. The proposed system achieved an average accuracy of 89% for forty static signs. This study will help the hearing impaired to learn new words used in their daily routine.

Sign Language Recognition, Microsoft Kinect, Hearing Impaired, Data Acquisition, Adaboost, Kinect Studio, Visual Gesture Builder

"Impact of Sign Language Recognition Systems in the Education of Hearing Impaired Students", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.901-905, December 2018, Available :http://www.jetir.org/papers/JETIREB06106.pdf

"Impact of Sign Language Recognition Systems in the Education of Hearing Impaired Students", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp901-905, December 2018, Available at : http://www.jetir.org/papers/JETIREB06106.pdf