Boykov Il'ya Vladimirovich, Doctor of physical and mathematical sciences, professor, head of sub-department of higher and applied mathematics, Penza State University (40 Krasnaya street, Penza, Russia), email@example.com
Ivanov Aleksandr Ivanovich, Doctor of engineering sciences, head of laboratory of biometric and neural network technologies, Penza Research Institute of Electrical Engineering (9 Sovetskaya street, Penza, Russia), firstname.lastname@example.org
Kalashnikov Dmitriy Mikhaylovich, Postgraduate student, Penza State University (40 Krasnaya street, Penza, Russia), email@example.com
Background. Main problems in development of algorithms and software for implementing voice authentication are the following: user's voice variations (voice can vary depending on health conditions, age, mood etc.); presence of a noise component. Solving these problems will allow to use the voice authentication technology to ensure the best protection of personal data, ease of usage. Besides, it is the cheapest among the existing identification technologies.
Materials and methods. The authors used numerical methods, digital signal processing, spectral methods, methods of mathematical statistics and time-series, as well as artificial intelligence and pattern recognition. A fragmentating device is based on a continuous-discrete model of speech processing, which, in combination with a narrow-band filter, allows to determine the average duration of sound.
Results. It is shown that the qualitative tone/noise speech qualifier should give the output of "0" and "1", the duration of which is described by the continuumdiscrete distribution of values of duration of the intervals between sections of tonal sounds, distributed according to normal laws. The discrete part of the distribution is formed by the discrete nature of the flow of tone sounds and noise appearance in speech, as well as their combinations (pairs, triples, quadruples, and etc). The continuous (continuum) part of sound length values distribution is conditioned by the instability of speech by changing a pronunciation pace. The article describes a method of calculating the average length of one sound of a meaningful speech. This study has allowed to build a machine to determine the average length of sound in different parts of an audio signal.
Conclusions. The article suggests a numerical algorithm for identification of individual speaker’s speech, allowing to sync speech areas. Usage of the developed algorithm has allowed to specify parameter values that characterize the statistical description of duration of the intervals between speech sounds and noise between tonal sounds. The study has made it possible to build a machine to determine the average length of sound in different parts of an audio signal. The results are the basis for building neural network authentication technologies.
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