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The emotion recognizer detects the user emotional state by extracting an emotion category from the voice signal and the dialogue history.
The emotion recognizer obtains the user emotional state from the acoustics of their utterance as well as the dialogue history.
Our main interest was to study negative user emotional states, mainly to detect frustration because of system malfunctions.
These states are defined as the combination of the user emotional state and the predicted intention according to their objective in the dialogue.
Their approach used social contacts based on the contact patterns that constructed based on user emotional states and behaviors from the mobile log.
For example, in emergency services [28] or intelligent tutors [29], it is necessary to know the user emotional state to calm them down, or to encourage them in learning activities.
Similar(54)
This new wave of research considers users' emotions explicitly to design interactive artifacts with the ability of estimating and responding to their users' emotional states.
Analysis of Variance models are employed to examine how various shape factors influence users' emotional responses.
Traditionally, most of designers only focus on satisfying users' functional needs and often ignore users' emotional and psychological needs.
Through presenting affective stimuli and empathic communication, computer agents are able to adjust to users' emotional states.
As smartphones become loaded with ever more sensors, and with software that can interpret their users' emotional states (see article), the scope for manipulating minds is growing.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com