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Acoustic Modeling for Emotion Recognition
This book presents state of art research in speech emotion recognition. Readers are first presented with basic research and applications - gradually more advance information is provided, giving readers comprehensive guidance for classify emotions through speech. Simulated databases are used and resu...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2015.
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| Edición: | 1st ed. 2015. |
| Colección: | SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 024 | 7 | |a 10.1007/978-3-319-15530-2 |2 doi | |
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| 100 | 1 | |a Anne, Koteswara Rao. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Acoustic Modeling for Emotion Recognition |h [electronic resource] / |c by Koteswara Rao Anne, Swarna Kuchibhotla, Hima Deepthi Vankayalapati. |
| 250 | |a 1st ed. 2015. | ||
| 264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2015. | |
| 300 | |a VII, 66 p. 24 illus., 17 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
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| 490 | 1 | |a SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning, |x 2191-7388 | |
| 505 | 0 | |a Introduction -- Emotion Recognition using Prosodic features -- Emotion Recognition using Spectral features -- Emotional Speech Corpora -- Classification Models -- Comparative Analysis of Classifiers in emotion recognition -- Summary and Conclusions. | |
| 520 | |a This book presents state of art research in speech emotion recognition. Readers are first presented with basic research and applications - gradually more advance information is provided, giving readers comprehensive guidance for classify emotions through speech. Simulated databases are used and results extensively compared, with the features and the algorithms implemented using MATLAB. Various emotion recognition models like Linear Discriminant Analysis (LDA), Regularized Discriminant Analysis (RDA), Support Vector Machines (SVM) and K-Nearest neighbor (KNN) and are explored in detail using prosody and spectral features, and feature fusion techniques. | ||
| 650 | 0 | |a Signal processing. | |
| 650 | 0 | |a Computational linguistics. | |
| 650 | 0 | |a User interfaces (Computer systems). | |
| 650 | 0 | |a Human-computer interaction. | |
| 650 | 0 | |a Acoustics. | |
| 650 | 1 | 4 | |a Signal, Speech and Image Processing . |
| 650 | 2 | 4 | |a Computational Linguistics. |
| 650 | 2 | 4 | |a User Interfaces and Human Computer Interaction. |
| 650 | 2 | 4 | |a Acoustics. |
| 700 | 1 | |a Kuchibhotla, Swarna. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 700 | 1 | |a Vankayalapati, Hima Deepthi. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783319155319 |
| 776 | 0 | 8 | |i Printed edition: |z 9783319155296 |
| 830 | 0 | |a SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning, |x 2191-7388 | |
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| 950 | |a Engineering (SpringerNature-11647) | ||
| 950 | |a Engineering (R0) (SpringerNature-43712) | ||