COMPARATIVE ANALYSIS OF VOCAL EMOTION RECOGNITION USING MACHINE LEARNING APPROACHES

Abstract

Abstract: The recognition of vocal emotions has gained significant attention in recent years due to its potential applications in human-computer interaction, affective computing, and psychological studies. Machine learning methodologies have emerged as effective tools for vocal emotion recognition, offering promising results. This paper presents a comprehensive review of the design of vocal emotion recognition systems using various machine learning approaches. The review compares different methodologies, evaluates speech databases using SWOT analysis, provides a comparative assessment, and presents analysis tables for a comprehensive understanding. Each section is elaborated with 3000 words, ensuring a detailed exploration of the topic.