Arabic sign language intelligent translator

ABSTRACT

Arabic sign language (ArSL) is method of communication between deaf communities in Arab countries; therefore, the development of systemsthat can recognize the gestures provides a means for the Deaf to easily integrate into society. In this research we implemented a computational structurefor an intelligent interpreter that automatically recognizes the isolated dynamic gestures. The proposed system recognizes and translates gesturesperformed with one or both hands. It comprises five subsystems, building dataset, video processing, feature extraction, mapping between ArSL and Arabictext, and text generation. To apply the system, 100-signs of ArSL was used, which was applied on 1500 video files. It's were divided into five classes:alphabet, numbers, "prepositions, pronouns and question words", Arabic life expressions, and "nouns and verbs". The evaluation indicated that thesystem automatically recognizes and translates isolated dynamic ArSL gestures by highly accurate manner. The results showed that the system accuracy is 95.8%.

KEYWORDS:

• Arabic sign language
• feature extraction
• key frame extraction
• isolated dynamic gestures
• machine learning
• video processing
• gray of co-occurrence matrix (GLCM)
• intelligent translation system

Acknowledgements

The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through General Research Project.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes on contributors

Abdelmoty M. Ahmed designed the research plan, organized and ran the experiments, contributed to the presentation, analysis and interpretation of the results, added, and reviewed genuine content where applicable.

Reda Abo Alez supervised the study and made considerable contributions to this research by critically reviewing the manuscript for significant intellectual content.

Gamal Tharwat supervised the study and made considerable contributions to this research by critically reviewing the manuscript for significant intellectual content.

Muhammad Taha presented idea and developed the theory and performed the computations and verified the analytical methods.

B. Belgacem made considerable contributions to this research by critically reviewing the literature review and the manuscript for significant intellectual content.

Ahmad M. J. Al Moustafa took the lead for writing the manuscript and provided critical feedback in the manuscript.

ORCID

Abdelmoty M. Ahmed http://orcid.org/0000-0002-3379-7314

Additional information

Funding

The funding was provided by the Deanship of Scientific Research at King Khalid University through General Research Project [grant number G.R.P-408-39].