Model for Automatic Speech Recognition Using Multi-Agent Recursive Cognitive Architecture

A concept of a fundamentally new approach to the development of speech recognition systems is proposed, as applications built based on existing approaches are not effective enough when used in noisy conditions and cocktail party situations. The architecture of the speech recognition system in an environment with several speakers based on multi-agent recursive cognitive models with imitation of the attention mechanism is constructed. The speech recognition system allows to model selectivity of perception in speech peculiarities for a speaker using multi-agent self-organization. Principles for selective signature processing inside sound modality are defined. They allow to tune on a speaker. Articulatory primitives were chosen as minimal functional pattern in the speech recognition problem. Due to multi-agent nature, use of space-time characteristics and self-learning this approach allow us to separate from each other and analyze sounds of different nature. Screenshots of the cognitive architecture of the speech recognition system based on multi-agent models of semantics are presented. (C) 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the 9th Annual International Conference on Biologically Inspired Cognitive Architectures.