Investigations of multimodal emotion recognition using deep learning techniques
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Abstract
Human emotions are essential to our lives, profoundly influencing
newlineour mental functions, behaviours, and social bonds. These emotional
newlineresponses are crucial in guiding decision-making skills, building interpersonal
newlinerelationships, and overall emotional health. Emotions are intricate and varied
newlineelements of human life, encompassing many personal experiences that
newlineexternal situations, internal thoughts, or physiological conditions can elicit.
newlineThey cover many emotions, such as happiness, sadness, anger, fear, surprise,
newlinedisgust, etc. Emotions are characterised by various factors, such as intensity,
newlineduration, and valence, ranging from positive to negative experiences.
newlineEmotion Recognition (ER) holds significant promise for
newlineinfluencing various aspects of human life, from Human-Computer Interaction
newline(HCI) to mental health, education, and business. The potential of
newlineunderstanding human emotions could lead to groundbreaking advancements
newlinein the development of empathetic and intelligent systems, enhancing life
newlineexperiences, promoting well-being, and facilitating meaningful interactions
newlinebetween people and technology. By enabling computers and virtual agents to
newlineanalyze and respond appropriately to users emotions, emotion recognition
newlinetechnology can make these systems more functional and intuitive. It offers
newlinenew possibilities such as personalized experiences, tailored product
newlinerecommendations, and empathetic support, inspiring a hopeful future for
newlinehuman-computer interaction.
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