Emotion detection of users is a challenging and exciting field where user's data is analyzed to recognize emotions such as happy, sad, angry etc. This data could be in one or multiple formats such as audio, video, text, still images etc. Relevant features are extracted and fused together to give a label. Fusing data from two or more sources(modalities) is another challenge, feature level or decision level fusion is employed. This paper inspects and studies the various approaches to multi-modal extraction of emotions.
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