Learning emotion-based acoustic features with deep belief networks

IEEE Workshop on Applications of Signal Processing to Audio and Acoustics

Volumn , Issue , 2011, Pages 65-68

  Schmidt, Erik M ^a   Kim, Youngmoo E ^a  

^a Drexel University   (United States)

Author keywords

deep belief networks; Emotion recognition; feature learning; regression

Indexed keywords

ACOUSTIC FEATURES; AUDIO FEATURES; AUTOMATIC DETECTION OF EMOTION; CLASSIFICATION PERFORMANCE; DIMENSIONALITY REDUCTION; EMOTION RECOGNITION; FEATURE DOMAIN; FEATURE LEARNING; FEATURE REPRESENTATION; HUMAN RESPONSE; MAGNITUDE SPECTRUM; NATURAL PROCESS; REGRESSION; SPECIFIC PROBLEMS; STOCHASTIC DISTRIBUTION; TIME VARYING; TIME WINDOWS;

FEATURE EXTRACTION; REGRESSION ANALYSIS; SIGNAL PROCESSING;

AUDIO ACOUSTICS;

EID: 83455238990     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ASPAA.2011.6082328     Document Type: Conference Paper

References (12)

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