Multimodal Data Analysis and Machine Learning Techniques: A Comparison and Review

Volume 20 No 22 (2022)

Mohd Usman Khan, Faiyaz Ahamad

DOI: 10.48047/nq.2022.20.22.NQ10420

Abstract

In the last few years, data analytics and machine learning have made immense progress in terms of technological advancements. It has become possible for machines and computers to have the ability to understand, recognize, and analyze emotions. We know that the affective reactions Fusion supports different methods in sentiment analysis research that uses audio, video, and text to predict fundamental emotions (anger, joy, sorrow, antipathy, fear, and surprise) researchers from different fields and disciplines are focused on emotional recognition. Multimodal analysis is always challenging for both devices and researchers

Keywords

Emotion recognition, effective computing, Data analytics, Machine learning, Multimodality

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