Abstract - This paper presents an overview of emotion recognition techniques using four different modalities: audio, video, EEG, and EMG. The ability to recognize emotions is a crucial aspect of human communication, and is becoming increasingly important in various fields such as psychology, medicine, and artificial intelligence. This paper presents a comprehensive review of emotion recognition techniques using four different modalities: audio, video, EEG, and EMG. We discuss the theoretical background and state-of-the-art methods used for emotion recognition in each modality, including feature extraction, data preprocessing, and machine learning algorithms. We also highlight the challenges and limitations of each modality, as well as the potential for future research. Emotion recognition is a crucial aspect of human communication and is becoming increasingly important in various fields such as psychology, medicine, and artificial intelligence.
Keywords—Audio signals ,Video signals, EEG signals,EMG signals,Featureextraction,Datapreprocessing,Machine learning, Neural networks, Support vector machines (SVMs)
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DOI:
10.17148/IJARCCE.2023.125183
