Prospects for Artificial Intelligence Technologies, Neural Networks and Computer Systems within the Development of Linguistics

This article describes the prospects of using artificial intelligence technologies, neural networks and computer systems for linguistic purposes. Systems and tools capable of analyzing linguistic units or generating texts of different composition and structure are listed. Morphological analysis systems such as Morfessor, Stanford Morphological Analyzer (SMA) and MyStem are disclosed. The features of the AOT (Automatic text processing) parser analyzer are discussed in detail. The scope of corpus analysis systems (AntConc) is given. A lot of attention is paid to NLP (Natural Language Processing) systems, capable of translating text into different languages (including gestures and sign languages), decoding written or typed fragments into a voice format, extracting key information from a text message, analyzing mood and emotions of the author of the statement based on verbal factors, interacting with users in a chat (based on NLP algorithms for understanding and answering user requests) and even modeling natural language, including syntax, grammar and semantics. In addition, the authors of the article propose a number of solutions suitable for eliminating some of the difficulties and problems in the use of neural networks and artificial intelligence systems.