Information System for Ukrainian Text Voiceover Based on Nlp and Machine Learning Methods

Abstract

During the research, an information system for voicing Ukrainian-language text was developed based on NLP and machine learning methods. The created information system is implemented in the form of a desktop application, which allows the process of voicing the Ukrainian-language text. The created system included all stages of software development: the design process, the implementation process, and the testing process. For the feasibility of creating this system, already existing software solutions on the market were analysed, their advantages and disadvantages were listed, which were subsequently taken into account to create a new system. During the system analysis of the system, a goal tree, a decision tree, and examples of context diagrams with process decomposition are given. One of the stages of the design of the economic part, where the budget that will be spent on the implementation of the system is analysed, all tax and administrative costs are calculated, development strategies are also analysed and the development strategy of the existing product with accompanying solutions and the product development strategy are selected. After that, an assessment was made for the feasibility of creating the designed system, it’s payback and profit. The object of the research is the process of the voiceover system of the Ukrainian-language text based on NLP and machine learning methods. The subject of the research is the methods and means of the Ukrainian-language text voicing system process based on NLP and machine learning methods. The purpose of the research is to create an information system for voicing Ukrainian- language text based on NLP and machine learning methods. The result of the work is a ready-to- implement information system for voicing Ukrainian-language text based on NLP and machine learning methods, an analytical review of literary and online sources related to the topic of voicing Ukrainian- language text based on NLP and machine learning methods, a systematic analysis of the research object, analysis and selection of software tools for system implementation, practical implementation of the system, economic justification of system implementation activities.