Buch, Englisch, 118 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 2117 g
Buch, Englisch, 118 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 2117 g
Reihe: SpringerBriefs in Speech Technology
ISBN: 978-1-4614-6359-7
Verlag: Springer US
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Geisteswissenschaften Sprachwissenschaft Computerlinguistik, Korpuslinguistik
- Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung
- Sozialwissenschaften Psychologie Allgemeine Psychologie Kognitionspsychologie Emotion, Motivation, Handlung
Weitere Infos & Material
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).
