Real-time Speech and Music Classification by Large Audio Feature Space Extraction

This book reports on an outstanding thesis that has significantly advanced the state-of-the-art in the automated analysis and classification of speech and music. It defines several standard acoustic parameter sets and describes their implementation in a novel, open-source, audio analysis framework c...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Eyben, Florian (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:Springer Theses, Recognizing Outstanding Ph.D. Research,
Temas:
Signal processing.
User interfaces (Computer systems).
Human-computer interaction.
Acoustical engineering.
Computational linguistics.
Signal, Speech and Image Processing .
User Interfaces and Human Computer Interaction.
Engineering Acoustics.
Computational Linguistics.
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Real-time Speech and Music Classification by Large Audio Feature Space Extraction  |h [electronic resource] /  |c by Florian Eyben. 
250 |a 1st ed. 2016. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2016. 
300 |a XXXVIII, 298 p. 41 illus., 39 illus. in color.  |b online resource. 
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490 1 |a Springer Theses, Recognizing Outstanding Ph.D. Research,  |x 2190-5061 
505 0 |a Abstract -- Introduction -- Acoustic Features and Modelling -- Standard Baseline Feature Sets -- Real-time Incremental Processing -- Real-life Robustness -- Evaluation -- Discussion and Outlook -- Appendix -- Mel-frequency Filterbank Parameters. 
520 |a This book reports on an outstanding thesis that has significantly advanced the state-of-the-art in the automated analysis and classification of speech and music. It defines several standard acoustic parameter sets and describes their implementation in a novel, open-source, audio analysis framework called openSMILE, which has been accepted and intensively used worldwide. The book offers extensive descriptions of key methods for the automatic classification of speech and music signals in real-life conditions and reports on the evaluation of the framework developed and the acoustic parameter sets that were selected. It is not only intended as a manual for openSMILE users, but also and primarily as a guide and source of inspiration for students and scientists involved in the design of speech and music analysis methods that can robustly handle real-life conditions. 
650 0 |a Signal processing. 
650 0 |a User interfaces (Computer systems). 
650 0 |a Human-computer interaction. 
650 0 |a Acoustical engineering. 
650 0 |a Computational linguistics. 
650 1 4 |a Signal, Speech and Image Processing . 
650 2 4 |a User Interfaces and Human Computer Interaction. 
650 2 4 |a Engineering Acoustics. 
650 2 4 |a Computational Linguistics. 
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830 0 |a Springer Theses, Recognizing Outstanding Ph.D. Research,  |x 2190-5061 
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950 |a Engineering (SpringerNature-11647) 
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