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Combined motion and voice analysis for the identification of persons with synergetic computers
With increasing computing power available, data stemming from different types of input sources can be used simultaneously to solve identification problems. Due to the independence of the different data sources, either lower error rates or a higher reliability of the results in comparison with simple optical lip reading can be expected. The classification of the preprocessed data is done by synergetic computers, which have recently attracted increasing attention as quick and robust algorithms for solving industrial classification tasks. As synergetic computers show a close mathematical similarity to self-organized phenomena in nature, they present a clear perspective for hardware realizations. In this paper the results of a large identification test with 101 different persons are presented.