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Emotion recognition is the process of identifying human emotion. People vary widely in their accuracy at recognizing the emotions of others. Use of technology to help people with emotion recognition is a relatively nascent research area. Generally, the technology works best if it uses multiple modalities in context.
Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.
Emotion recognition in conversation (ERC) is a sub-field of emotion recognition, that focuses on mining human emotions from conversations or dialogues having two or more interlocutors. [1] The datasets in this field are usually derived from social platforms that allow free and plenty of samples, often containing multimodal data (i.e., some ...
Sentiment and emotion characteristics are prominent in different phonetic and prosodic properties contained in audio features. [14] Some of the most important audio features employed in multimodal sentiment analysis are mel-frequency cepstrum (MFCC), spectral centroid, spectral flux, beat histogram, beat sum, strongest beat, pause duration, and pitch. [3]
Emotion perception refers to the capacities and abilities of recognizing and identifying emotions in others, in addition to biological and physiological processes involved. . Emotions are typically viewed as having three components: subjective experience, physical changes, and cognitive appraisal; emotion perception is the ability to make accurate decisions about another's subjective ...
Emotional intelligence (EI), also known as emotional quotient (EQ), is the ability to perceive, use, understand, manage, and handle emotions.High emotional intelligence includes emotional recognition of emotions of the self and others, using emotional information to guide thinking and behavior, discerning between and labeling of different feelings, and adjusting emotions to adapt to environments.
Emotion-oriented computing (or "affective computing") is gaining importance as interactive technological systems become more sophisticated. Representing the emotional states of a user or the emotional states to be simulated by a user interface requires a suitable representation format; in this case a markup language is used.
In terms of the study or recognition of emotions through voice, this can be carried out in multiple ways. The main method of strategy for recognising emotion through voice is labelling and categorising which vocal expression matches which emotional stimuli (for example, happiness, sadness or fear).