Ebook: Robust Emotion Recognition using Spectral and Prosodic Features
- Tags: Signal Image and Speech Processing, User Interfaces and Human Computer Interaction, Language Translation and Linguistics, Computational Linguistics
- Series: SpringerBriefs in Electrical and Computer Engineering
- Year: 2013
- Publisher: Springer-Verlag New York
- Edition: 1
- Language: English
- pdf
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.
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.
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.
Content:
Front Matter....Pages i-xii
Introduction....Pages 1-15
Robust Emotion Recognition using Pitch Synchronous and Sub-syllabic Spectral Features....Pages 17-46
Robust Emotion Recognition using Sentence, Word and Syllable Level Prosodic Features....Pages 47-69
Robust Emotion Recognition using Combination of Excitation Source, Spectral and Prosodic Features....Pages 71-84
Robust Emotion Recognition using Speaking Rate Features....Pages 85-94
Emotion Recognition on Real Life Emotions....Pages 95-100
Summary and Conclusions....Pages 101-107
Back Matter....Pages 109-118
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.
Content:
Front Matter....Pages i-xii
Introduction....Pages 1-15
Robust Emotion Recognition using Pitch Synchronous and Sub-syllabic Spectral Features....Pages 17-46
Robust Emotion Recognition using Sentence, Word and Syllable Level Prosodic Features....Pages 47-69
Robust Emotion Recognition using Combination of Excitation Source, Spectral and Prosodic Features....Pages 71-84
Robust Emotion Recognition using Speaking Rate Features....Pages 85-94
Emotion Recognition on Real Life Emotions....Pages 95-100
Summary and Conclusions....Pages 101-107
Back Matter....Pages 109-118
....