Abstract

The article analyzes and investigates directions for improving the quality characteristics of voice authentication systems in various access systems by improving the procedures for pre-processing registration materials. One of the main ways of improving the quality characteristics of user authentication systems, which was studied in the work, is the use of phase information of the voice signal. The actual scientific task of researching new procedures for pre-processing the voice signal of the user of the authentication system is being solved. The purpose of this work is to develop additional preprocessing procedures to reduce noise in voice signals of the authentication system. Refinement of pre-processing procedures was carried out based on the use of phase data of the voice signal. The results are obtained in the process of statistical analysis of simulation results using experimental model data of the authentication system. The phase space of the voice signal allows you to expand the possibilities of pre-processing due to the use of a priori information about the nature of changes in phase data. The scientific novelty of the obtained results lies in the fact that for the first time, a technique was developed, and experimental studies were carried out for the pre-processing of the user’s voice signal using the space of phase data. The practical significance of the obtained results is as follows: the phase information approximation interval was selected taking into account a priori data on the nature of its changes; an original linear approximation of phase data containing one harmonic of a voice signal is proposed; a mechanism for determining two harmonics in the phase data of a voice signal when using the proposed linear approximation is developed; the conducted experimental studies allow to develop a mechanism for compensation of random errors in registration materials. The presented research results are advisable for use in voice authentication systems, improvement of speech recognition systems, and solving speaker identification tasks.

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