Neuron-Like Approach to Speech Recognition (original) (raw)

Abstract

In this paper, we present a new approach to speech recognition based on A. Zhdanov’s biomorphic neuron-like networks, which is also known as the autonomous adaptive control (AAC) method. In contrast to artificial neural networks (ANNs), a neuron in the AAC method is itself a self-learning pattern recognition system. We attempt to build a speech recognition system as a construction of such neurons without a program component. If this attempt is successful, then we will be able to simulate the natural principle of speech recognition not only in a program way but also via parallel hardware implementations. We understand the speech recognition problem as one of the speech processes in natural nervous systems that is to be simulated.

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Authors and Affiliations

  1. Moscow Institute of Physics and Technology, Institutskii per. 9, Dolgoprudnyi, Moscow oblast, 141701, Russia
    N. N. Diep
  2. Lebedev Institute of Precision Mechanics and Computer Engineering, Russian Academy of Sciences, Leninskii pr. 51, Moscow, 119991, Russia
    A. A. Zhdanov

Authors

  1. N. N. Diep
  2. A. A. Zhdanov

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Correspondence toN. N. Diep.

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Original Russian Text © N.N. Diep, A.A. Zhdanov, 2018, published in Programmirovanie, 2018, Vol. 44, No. 3.

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Diep, N.N., Zhdanov, A.A. Neuron-Like Approach to Speech Recognition.Program Comput Soft 44, 170–180 (2018). https://doi.org/10.1134/S0361768818030088

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