Challenges in real-life emotion annotation and machine learning based detection

Neural Networks

Volumn 18, Issue 4, 2005, Pages 407-422

  Devillers, Laurence ^a   Vidrascu, Laurence ^a   Lamel, Lori ^a  

^a CNRS   (France)

Author keywords

Blended emotion; Decision trees; Emotion annotation; Emotion detection; Machine learning; Naturalistic spoken data; Prosodic, disfluency and lexical features; SVM

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER SCIENCE; DATA ACQUISITION; LEARNING SYSTEMS; NEURAL NETWORKS;

ARTIFICIAL DATA; HUMAN BEHAVIOR; NEUROSCIENCE;

BEHAVIORAL RESEARCH;

ARTICLE; ASSOCIATION; BEHAVIOR; CLASSIFICATION; EMOTION; LANGUAGE ABILITY; LEARNING; MACHINE; MATHEMATICAL ANALYSIS; NEUROSCIENCE; NONVERBAL COMMUNICATION; PRIORITY JOURNAL; RHYTHM; SPEECH ARTICULATION;

ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; EMOTIONS; EXPRESSED EMOTION; HUMANS; LIFE; MODELS, PSYCHOLOGICAL; PATTERN RECOGNITION, AUTOMATED; SIGNAL DETECTION (PSYCHOLOGY); VERBAL BEHAVIOR;

EID: 21544459345     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2005.03.007     Document Type: Article

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