(untitled) (Computer systems and information technologies, 2022)
The proposed architecture of the identification software system in the form of class and sequence diagrams. The main criteria for assessing the accuracy of speaker identification were studied and possible sources of loss of speaker identification accuracy were identified, which can be used when building a speaker identification system. A software system based on the proposed architecture and previously developed identification algorithms and methods was created. The following conclusions can be drawn on the basis of the performed research: approaches to the construction of existing announcer identification systems are considered; the main criteria for assessing the accuracy of announcer identification were investigated and the main sources of loss of accuracy during announcer identification were identified; the structural construction of the announcer identification system is considered, taking into account the identified sources of loss of accuracy during announcer identification; the proposed architecture of the speaker identification system in the UML language in the form of class and sequence diagrams; a software system was built that implements the functions of speech signal identification according to the methods and algorithm proposed in previous works. The software system uses a ranking method based on three different criteria. These include: calculation of the proximity of two-dimensional probability density function curves for the frequency of the main tone and the location in the spectrum of three frequency ranges that are extracted from the speech recorded in the speech signal; calculation of the proximity of the probability density function curves for each of these features separately; calculation of the degree of closeness of the absolute maxima of the formant spectra extracted from the speech recorded in the speech signal.