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...

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Bibliographic Details
Main Authors: Rao, K. Sreenivasa. (Author), Koolagudi, Shashidhar G. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic
Language:English
Published: New York, NY : Springer New York : Imprint: Springer, 2013.
Series:SpringerBriefs in Electrical and Computer Engineering,
Subjects:
Online Access:https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4614-6360-3
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505 0 # |a 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). 
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