Open AccessSign language recognition through Leap Motion controller and input prediction algorithm
Author(s) -
Daniyar Enikeev,
Светлана Мустафина
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1715/1/012008
Subject(s) - sign language , computer science , sign (mathematics) , perspective (graphical) , speech recognition , motion (physics) , artificial neural network , artificial intelligence , american sign language , natural language , algorithm , linguistics , mathematics , mathematical analysis , philosophy
The sign recognition systems are aimed to help deaf people communicate with society. In this paper we proposed our own concept of sign language recognition, which is based on a co-operative deep learning neural network, a text input prediction algorithm and a feedback from the user. We have pointed out the complexity of the Russian sign language and conceived the fingerspelling recognition. The method utilizes the natural properties of fingerspelling in order to increase the accuracy and recognition performance by predicting the ongoing letter. We also provide a detailed review of data acquisition in the related works. From a hardware perspective, we suggest using Leap Motion controller.