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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| Main Authors: | , |
|---|---|
| Format: | Livre numérique |
| Language: | Anglais |
| Published: |
New York, NY :
Springer New York
2013.
Cham : Springer Nature |
| Series: | SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning
|
| Online Access: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Robust Emotion Recognition using Spectral and Prosodic Features, Texte imprimé, 9781461463597 • Robust Emotion Recognition using Spectral and Prosodic Features, Texte imprimé, 9781461463610 |
Table of Contents:
- 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).