A Proposed Standardization for Arabic Sign Language Benchmark Database | ||||
| The Egyptian Journal of Language Engineering | ||||
| Article 1, Volume 2, Issue 1, April 2015, Page 1-9 PDF (768.82 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/ejle.2015.60253 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Ahmed Samir  1; Mohamed Fahmi Tolba2
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| 1Faculty of Computer and Information Science, Ain Shams University, Cairo, Egypt | ||||
| 2Faculty of Computers& Information Technology, Ain Shams University | ||||
| Abstract | ||||
| This The lack of a visualized representation for standard Arabic Sign Language (ArSL) makes it difficult to do something as commonplace as looking up an unknown word in a dictionary. The majority of printed dictionaries organize ArSL signs (represented in drawings or pictures) based on their nearest Arabic translation; so unless one already knows the meaning of a sign, dictionary look-up is not a simple proposition. In this paper we introduce the ASL database, a large and expanding public dataset containing video sequences of thousands of distinct ArSL signs. This dataset is being created as part of a project to develop an Arabic sign language translator. At the same time, the dataset can be useful for benchmarking a variety of computer vision and machine learning methods designed for learning and/or indexing a large number of visual classes especially approaches for analyzing gestures and human communication. | ||||
| Keywords | ||||
| Arabic Sign Language (ARSL); Arabic Sign Language Database; Database Benchmark | ||||
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