Detection of sign language gesture using deep learning and machine learning

Detection of sign language gesture using deep learning and machine learning

Prajwal naik, Nitin Chavan, Piyush Jadhav, Niranjan khavale

Kj’s Trinity college of engineering and research pune

Abstract—

Sign language is used as a primary form of communication by many people who are Deaf, deafened, hard of hearing, and non- verbal. Communication barriers exist for members of these populations during daily interactions with those who are unable to understand or use sign language. Based on the depth information of Kinect, this paper studies the real-time dynamic sign language recognition algorithm and improves the dynamic time warping algorithm for the recognition of sign language trajectories. As of the authors knowledge, little to no work exists in the detection of phonetic characteristics in SL, and there is little consensus on what may constitute a phoneme in SL linguistics. In this regard, this work may contribute to further understand the building blocks of SL utterance formation, which may have direct repercussions on how SLs are represented, transmitted and processed electronically.

Index Terms—Sign Language, Clustering, Naive Bayes, Natural Language Processing, Image Thresholding.