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.
Highlights
Arabic Sign language is different in each Arab region or/and country with many dialects
A need appeared to unify Arabic sign language in all Arabian countries. This derived the Council of Arab Ministers of Social Affairs (CAMSA) to take a decision of developing a unified Arab sign language dictionary and publish it to all countries, in an attempt to help Arab deaf people to have a common language in addition to their local language [1]
Arabic word order is so flexible that it allows for one meaning to be expressed in different formal structures, such as V-S-O, S-V-O, O-V-S, V-O-S. This makes the structure of Arabic sign languages (ARSLs) familiar, especially to hearing learners, and comprehensible to the uneducated because of their grammatical simplicity, which does not exist in standard Arabic
Summary
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.
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