ANALYSIS OF TTS TECHNOLOGIES AND IMPLEMENTATION OF AN ADAPTIVE INTELLIGENT LEARNING SYSTEM BASED ON LSTM

Abstract

This article provides a comprehensive review of the current state and functional capabilities of Text-to-Speech (TTS) technologies. The analysis covers speech quality, language support, parametric flexibility, and technical integration possibilities of various TTS services, as well as their potential applications in the field of education. The conducted analysis demonstrates that TTS technologies can play a significant role in narrating educational materials, supporting users with special educational needs, and enhancing digital learning environments. Furthermore, the study investigates the architecture and operating principles of the Long Short-Term Memory (LSTM) neural network. The LSTM model’s ability to efficiently process temporal dependencies substantiates its suitability for use in adaptive learning systems. This model enables the analysis of students’ learning dynamics, considers their previous actions, and facilitates the creation of individualized learning trajectories. The results of this study indicate that the integration of TTS and LSTM technologies represents a promising direction for the development of modern, adaptive, and user-centered learning systems and may serve as a foundation for further research in this area.