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The interaction between human beings and computers will be more natural if computers are able to perceive and respond to human non-verbal communication such as emotions. Although several approaches have been proposed to recognize human emotions based on facial expressions or speech, relatively limited work has been done to fuse these two, and other,(More)
—During expressive speech, the voice is enriched to convey not only the intended semantic message but also the emotional state of the speaker. The pitch contour is one of the important properties of speech that is affected by this emotional modulation. Although pitch features have been commonly used to recognize emotions, it is not clear what aspects of the(More)
Automated emotion state tracking is a crucial element in the computational study of human communication behaviors. It is important to design robust and reliable emotion recognition systems that are suitable for real-world applications both to enhance analytical abilities to support human decision making and to design human–machine interfaces that facilitate(More)
Recognizing human emotions/attitudes from speech cues has gained increased attention recently. Most previous work has focused primarily on suprasegmental prosodic features calculated at the utterance level for modeling against details at the segmental phoneme level. Based on the hypothesis that different emotions have varying effects on the properties of(More)
Since emotions are expressed through a combination of verbal and non-verbal channels, a joint analysis of speech and gestures is required to understand expressive human communication. To facilitate such investigations, this paper describes a new corpus named the " interactive emotional dyadic motion capture database " (IEMOCAP), collected by the Speech(More)
Improvised acting is a viable technique to study human communication and to shed light into actors' creativity. The USC CreativeIT database provides a novel bridge between the study of theatrical improvisation and human expressive behavior in dyadic interaction. The theoretical design of the database is based on the well-established improvisation technique(More)
Emotion expression is an essential part of human interaction. Rich emotional information is conveyed through the human face. In this study, we analyze detailed motion-captured facial information of ten speakers of both genders during emotional speech. We derive compact facial representations using methods motivated by Principal Component Analysis and(More)
Research on human emotional behavior, and the development of automatic emotion recognition and animation systems, rely heavily on appropriate audiovisual databases of expressive human speech, language, gestures and postures. The use of actors to record emotional databases has been a popular approach in the study of emotions. Recently, this method has been(More)
In the study of expressive speech communication, it is commonly accepted that the emotion perceived by the listener is a good approximation of the intended emotion conveyed by the speaker. This paper analyzes the validity of this assumption by comparing the mismatches between the assessments made by na¨ıve listeners and by the speakers that generated the(More)
—An appealing scheme to characterize expressive behaviors is the use of emotional dimensions such as activation (calm versus active) and valence (negative versus positive). These descriptors offer many advantages to describe the wide spectrum of emotions. Due to the continuous nature of fast-changing expressive vocal and gestural behaviors, it is desirable(More)