An intelligent system of analysis of intonation structures: application in teaching the Russian language to the Chinese language native speakers

This paper describes the development of a program for analysis of intoning of verbal pieces in the Russian language. The goal is to measure the differences between the intoning of verbal pieces by both native and international Russian language speakers. The research methodology is based on the application of neural network analysis for solving the task of identification of speech samples, obtained by recording inophones’ speech. The experiment was carried out with the participation of 12 people: native speakers of the Russian language and the Chinese language, both male and female, aged from 20 to 35. A total number of speech samples amounted to 4800 items. Overall, 10 speech items in declarative and interrogative intonation were analyzed. A neural network that provides an assessment of correspondence of a speech sample to the standard variant of intoning was formed and trained. The results of experimental research are presented in the form of statistical assessments of pronouncing the verbal pieces with various intonations. These results are recommended to be applied in the process of learning Russian as a foreign language: the obtained data are considered as the confidence threshold of intoning identification, which complies with the standard or deviates from it. The results can also be applied for the individualized automated compilation of recommendations on correction of mistakes.