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This article reports on an extensive database of American Sign Language (ASL) motions, handshapes, words and sentences. Research on automatic recognition of ASL requires a suitable database for the training and the testing of algorithms. The databases that are currently available do not allow for algorithmic development that requires a step-by-step approach to ASL recognition-from the recognition of individual handshapes, to the recognition of motion primitives, and finally, to the recognition of full sentences. We have sought to remove these deficiencies in a new database-the Purdue RVL-SLLL ASL database.
Martı́nez et al. (Wed,) studied this question.