Artificial intelligence

Abstract: The article considers the actual scientific and technical problem of developing an intelligent system for automatic summarization and analysis of text and audiovisual content. In the context of exponential growth of digital information volumes, there is an urgent need for tools that allow fast extraction of the content core from unstructured data. The authors propose a web application architecture based on the ASP.NET Core platform using modern natural language processing (NLP) models. Mechanisms for integrating cloud computing and intelligent APIs to ensure high accuracy of information compression are studied. The software solution is based on the client-server architecture with the implementation of real-time protocols for two-way data exchange. The paper details approaches to speech-to-text conversion with subsequent semantic analysis. The research results can be implemented in educational processes, business analytics, and government institutions to increase the efficiency of working with information flows.

Keywords: intelligent systems, natural language processing, automatic summarization, cloud services, neural networks, language models, ASP.NET Core, SignalR

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