Current Trends in the Use of Machine Learning for Error Correction in Ukrainian Texts

The article's authors have provided a detailed problem description of identifying and correcting errors in Ukrainian-language texts. This paper provides a detailed analysis of the latest research and publications aimed at solving the problems of identifying and correcting errors in Ukrainian-language texts. The analysis of modern tools related to error correction in texts is presented along with a comparative description. Investigated the existing data corpora for the Ukrainian language so that they are relevant to solving GEC tasks. Discovered the need to create a large annotated data corpus, which will be prepared by a special team with linguistic expertise. Analysed the opportunities, advantages and disadvantages of modern machine learning models that interpret the task of detecting and correcting errors in texts as classification or machine translation. Introduced the need to develop a machine-learning algorithm that will take into account the specifics of morphologically complex languages, such as Ukrainian. Demonstrated the work of the modern models and provided screenshots. Revealed the need for further research in the Ukrainian segment of machine learning to solve the problems of correcting errors in texts using various methods and approaches.