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This paper reviews the extensive state of the art in automated recognition of continuous signs, from different languages, based on the data sets used, features computed, technique used, and recognition rates achieved. We find that, in the past, most work has been done in finger-spelled words and isolated sign recognition, however recently, there has been… (More)
This paper focuses on applying segmentation and unsu-pervised learning algorithms to create an accurate sign language recognition model.