Robust Emotion Recognition using Spectral and Prosodic Features - Info and Reading Options
By K. Sreenivasa Rao
"Robust Emotion Recognition using Spectral and Prosodic Features" was published by Springer New York in 2013 - New York, NY, it has 118 pages and the language of the book is English.
“Robust Emotion Recognition using Spectral and Prosodic Features” Metadata:
- Title: ➤ Robust Emotion Recognition using Spectral and Prosodic Features
- Author: K. Sreenivasa Rao
- Language: English
- Number of Pages: 118
- Publisher: Springer New York
- Publish Date: 2013
- Publish Location: New York, NY
“Robust Emotion Recognition using Spectral and Prosodic Features” Subjects and Themes:
- Subjects: ➤ Engineering - Translators (Computer programs) - Computer science - Language Translation and Linguistics - Image and Speech Processing Signal - User Interfaces and Human Computer Interaction - Computational linguistics - Speech processing systems - Pattern recognition systems - Spectral analysis (Phonetics) - Prosodic analysis (Linguistics) - Linguistic analysis (linguistics)
Edition Specifications:
- Format: [electronic resource] /
- Pagination: ➤ XII, 118 p. 37 illus., 15 illus. in color.
Edition Identifiers:
- The Open Library ID: OL27085854M - OL19900199W
- Library of Congress Control Number (LCCN): 2012954864
- ISBN-13: 9781461463603
- All ISBNs: 9781461463603
AI-generated Review of “Robust Emotion Recognition using Spectral and Prosodic Features”:
"Robust Emotion Recognition using Spectral and Prosodic Features" Table Of Contents:
- 1- Introduction
- 2- Robust Emotion Recognition using Pitch Synchronous and Sub-syllabic Spectral Features
- 3- Robust Emotion Recognition using Word and Syllable Level Prosodic Features
- 4- Robust Emotion Recognition using Combination of Excitation Source, Spectral and Prosodic Features
- 5- Robust Emotion Recognition using Speaking Rate Features
- 6- Emotion Recognition on Real Life Emotions
- 7- Summary and Conclusions
- 8- MFCC Features
- 9- Gaussian Mixture Model (GMM).
"Robust Emotion Recognition using Spectral and Prosodic Features" Description:
The Open Library:
<p>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.</p><p>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.</p>
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