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    Multi-sensorial inputs for the identification of persons with synergetic computers

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    We present an approach to combine the optical motion analysis of the lips and acoustic voice analysis of defined single words for identifying the people speaking. Due to the independence of the different data sources, a higher reliability of the results in comparison with simple optical lip reading is observed. The classification of the preprocessed data is done by synergetic computers, which have recently attracted increasing attention as robust algorithms for solving industrial classification tasks. Special potential of synergetic computers lies in their close mathematical similartiy to self-organized phenomena in nature. Therefore they present a clear perspective for hardware realizations. We propose that the combination of motion and voice analysis offers a possibility for realizing robust access control systems
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