A Survey of Deep Learning Techniques for Speech Emotion Recognition

Speech emotion recognition (SER) is vital for interpreting a speaker's emotional state through audio analysis. By categorizing emotions like anger, happiness, and sadness, SER unlocks insights into thoughts and well-being. Leveraging speech as a fundamental and efficient mode of communication, extensive research has focused on developing automated voice-based emotion recognition systems to enhance human-machine interaction. Voice is increasingly central to Human-Machine Interfaces, a multidisciplinary field integrating computer science, signal processing, and psychology. Advancements in this area enable more seamless communication, with speech recognition capturing both linguistic content and emotional nuances, establishing its significance in human-machine communication systems. Keywords: - SER, SVM, ML, speech, deep learning, CNN.