Design of ASR Software for Recognition of the Russian Language Variants

The article first touches on the problem of speech recognition of Russian language variants. With the development and growing (ASR) popularity of the automatic speech recognition (ASR) technology, more and more attention is now being paid to the problems related to the incompatibility of modern applications to work with non-standard language varieties. This question is especially relevant for Russian, as it is, contrary to the conservative statement about its homogeneity, represented by many forms that differ from the standard one, which generally have a wide distribution in various regions of Russia and throughout the world. The study of various aspects of the interaction of ACER algorithms with non-standard varieties of the Russian language, as well as existing approaches to creating an ASR product that can process such idioms, today seems to be an urgent direction. The aim of the work is to analyze in detail the methods for developing ASR systems capable of performing the task of recognizing and processing speech samples of speakers of Russian language forms different from the standard, which may contribute to further research on this topic. The research material is based on the software interface of the SOVA ASR application for automatic speech recognition, as well as a selection of audio recordings of speech of native speakers of the Central Asian and Ukrainian versions of Russian, and the corresponding transcription texts. The research methods such as the study and analysis of specialized literature, data collection for subsequent software processing, qualitative and quantitative analysis, and experimental data are used.