Abstract
The monograph discusses the theory, algorithms and practical methods of implementing digital processing and recognition of speech signals. The basics of mathematical analysis of digital signals necessary for speech processing are presented. The acoustic theory of speech formation with the construction of a general discrete model is briefly described. The main characteristic features of speech signals, as well as methods of their isolation are considered. Hidden Markov models and the architecture of traditional recognition systems based on them are described in detail. Weighted finite converters used to increase the efficiency and speed up the process of decoding acoustic signals are considered. The main architectures of artificial neural networks and examples of integrated (end-to-end) speech recognition systems based on them are presented. It is intended for students, postgraduates, researchers and specialists dealing with speech signal processing, pattern recognition and artificial intelligence.
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