A comparison of feature extraction techniques for speech emotion identification

Abstract

Speech Emotion Recognition (SER) is an essential component in human-computer interaction, enhancing the machine's ability to understand and respond to human emotions. This research paper presents a comparative study of various feature extraction techniques used in SER. By evaluating the performance of different methods, we aim to identify the most effective approaches for accurately recognizing emotions from speech. The study focuses on traditional and advanced techniques, comparing their efficacy through extensive experiments on standard datasets.