COMPUTER VOICE CONTROL SYSTEM

Authors

Ashurova Shabnam Nurulloevna – Senior Lecturer of the Department of Programming and Information Systems, Polytechnic Institute of the Technical University of Tajikistan named after Academician M.S. Osimi, Khujand, Republic of Tajikistan, sh.nurulloevna@gmail.com Solieva Mehrangez Tolibovna. – PhD student, Department of Programming and Information Systems, Polytechnic Institute of Tajik Technical University named after academician M.S. Osimi, Khujand, Republic of Tajikistan, smehrangez92@gmail.com

Abstract

The article discusses methods for organizing an automatic speech recognition system based on the combined use of neural networks and hidden Markov models. The proposed hybrid system, consisting of a neural network model and hidden Markov models (NN/HMM), utilizes an artificial neural network for voice analysis and Markov models for language recognition. Voice control and its application on personal computers represent an important challenge. The article analyzes the main algorithms for speech recognition. The development and creation of efficient speech recognition and voice control systems represent a significant challenge, as their implementation forms the basis of a full-fledged voice interface that opens a wide range of possibilities for users. One of the most effective approaches is the use of a hybrid system that combines neural networks (NN) and hidden Markov models (HMM). This method allows for the advantages of both approaches: neural networks provide more accurate identification of voice сharacteristics, while hidden Markov models help process sound sequences and maintain the correct order of words.

Keywords

аutomatic speech recognition, hidden Markov model, neural networks, recognition system, computer tools, voice control, voice commands.

References

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Publish date

2026-03-25