ANALYSIS OF EMOTIONS USING VOICE FEATURES

The paper describes methods for recognizing human emotions. This area of artificial intelligence is developing rapidly and plays a key role in improving the efficiency of human-computer interaction. The study analyzes existing approaches to recognizing emotions using voice features. This paper discusses methods for analyzing emotions based on voice features. The main parameters, such as frequency, tempo, intonation, timbre, and volume, are described, which make it possible to determine the emotional state of a person by his or her speech. Modern approaches are discussed, including the use of machine learning algorithms and neural network models for processing audio files and classifying emotions. This study contributes to the development of emotion research by providing a deeper understanding of human emotional states.