Affective natural language generation
Affective interactions
User Modeling and User-Adapted Interaction
Automatic inference of complex affective states
Computer Speech and Language
Towards Systems That Care: A Conceptual Framework based on Motivation, Metacognition and Affect
International Journal of Artificial Intelligence in Education
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This study focuses on the perception of emotion and attitude in speech. The ability to identify vocal expressions of emotion and/or attitude in speech material was investigated. Systematic perception experiments were carried out to determine optimal values for the acoustic parameters: pitch level, pitch range and speech rate. Speech was manipulated by varying these parameters around the values found in a selected subset of the speech material which consisted of two sentences spoken by a male speaker expressing seven emotions or attitudes: neutrality, joy, boredom, anger, sadness, fear, and indignation. Listening tests were carried out with this speech material, and optimal values for pitch level, pitch range, and speech rate were derived for the generation of speech expressing emotion or attitude, from a neutral utterance. These values were perceptually tested in re-synthesized speech and in synthetic speech generated from LPC-coded diphones.