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Robust Emotion Recognition using Spectral and Prosodic Features

by Rao, K. Sreenivasa.
Authors: Koolagudi, Shashidhar G.%author. | SpringerLink (Online service) Series: SpringerBriefs in Electrical and Computer Engineering, 2191-8112 Physical details: XII, 118 p. 37 illus., 15 illus. in color. online resource. ISBN: 1461463602 Subject(s): Engineering. | Computer science. | Translators (Computer programs). | Computational linguistics. | Engineering. | Signal, Image and Speech Processing. | User Interfaces and Human Computer Interaction. | Language Translation and Linguistics. | Computational Linguistics.
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E-Book E-Book AUM Main Library 621.382 (Browse Shelf) Not for loan

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).

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 complementary evidences obtained from excitation source, vocal tract system and prosodic features for the purpose of enhancing emotion recognition performance. Features based on speaking rate characteristics are explored with the help of multi-stage and hybrid models for further improving emotion recognition performance. Proposed spectral and prosodic features are evaluated on real life emotional speech corpus.

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