Publication: Research and Development of Autonomous Neuromorphic Speech Stress Detector Based on Spike Representation of Information
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2020
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© 2020 IEEE.The paper presents the results of a comparative designs analysis of known neuromorphic FEE (Front End Electronics) for the primary adaptive time-frequency conversion of sound information into multidimensional streams of electrical signals as well as secondary data processing to identify characteristic features and determine the emotional component in the original speech signal based on analog CMOS circuits, switched capacitor circuits, digital FPGAs. The perspective directions of SSD (Speech Stress Detector) development on the basis of combined technologies of analog-digital CMOS and memristive elements are proved. The developed SSD prototype based on memristive analog-digital spike neural network is characterized by active FEE dynamics close to Hopf bifurcation, self-learning and adaptation in secondary information processing.
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Arkhangelsky, V. G. Research and Development of Autonomous Neuromorphic Speech Stress Detector Based on Spike Representation of Information / Arkhangelsky, V.G., Alyushin, S.A., Alyushin, A.V. // Proceedings of the 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, EIConRus 2020. - 2020. - P. 1746-1754. - 10.1109/EIConRus49466.2020.9039345