Robust Emotion Recognition using Spectral and Prosodic Features

In this brief, the authors discuss recently explored spectral (sub-segmental and pitch synchronous) and prosodic (global and local features at word and syllable levels in different parts of the utterance) features for discerning emotions in a robust manner. The authors also delve into the complement...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Rao, K. Sreenivasa (Συγγραφέας), Koolagudi, Shashidhar G. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: New York, NY : Springer New York : Imprint: Springer, 2013.
Σειρά:SpringerBriefs in Electrical and Computer Engineering,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Introduction
  • Robust Emotion Recognition using Pitch Synchronous and Sub-syllabic Spectral Features
  • Robust Emotion Recognition using Word and Syllable Level Prosodic Features
  • Robust Emotion Recognition using Combination of Excitation Source, Spectral and Prosodic Features
  • Robust Emotion Recognition using Speaking Rate Features
  • Emotion Recognition on Real Life Emotions
  • Summary and Conclusions
  • MFCC Features
  • Gaussian Mixture Model (GMM).