error identification

The problem of automated error detection in Ukrainian texts is becoming particularly relevant in the context of the growth of digital content. A mathematical model of a decision support system for detecting errors in Ukrainian-language texts has been developed. The process of error identification has been studied as a multi-class classification task at the token level, considering the context of the text. The use of probabilistic models has been proposed to determine the type of error depending on the environment of tokens in the text.

This paper presents the concept and technical justification of a software product for automatic detection and correction of spelling errors in German-language texts. The relevance of the topic is due to the complexity of the German language in terms of grammar, spelling and word formation, which creates significant difficulties for speakers of other languages. This is especially true for those who study the language or use it in professional activities, where the accuracy of speech is crucial.