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

(Autor)

Buch | Hardcover
XXXVIII, 298 Seiten
2016 | 1st ed. 2016
Springer International Publishing (Verlag)
978-3-319-27298-6 (ISBN)

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Real-time Speech and Music Classification by Large Audio Feature Space Extraction - Florian Eyben
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This book reports on an outstanding thesis thathas significantly advanced the state-of-the-art in the automated analysis andclassification of speech and music.  Itdefines several standard acoustic parameter sets and describes theirimplementation in a novel, open-source, audio analysis framework calledopenSMILE, which has been accepted and intensively used worldwide. The bookoffers extensive descriptions of key methods for the automatic classificationof speech and music signals in real-life conditions and reports on theevaluation of the framework developed and the acoustic parameter sets that wereselected. It is not only intended as a manual for openSMILE users, but also andprimarily as a guide and source of inspiration for students and scientists involvedin the design of speech and music analysis methods that can robustly handlereal-life conditions.

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.

Erscheinungsdatum
Reihe/Serie Springer Theses
Zusatzinfo XXXVIII, 298 p. 41 illus., 39 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Themenwelt Technik Elektrotechnik / Energietechnik
Schlagworte Acoustic Feature Extraction • Affective computing • Computational Linguistics • Computational Paralinguistics • Engineering • Engineering Acoustics • Music Information Retrieval • openSMILE • Signal, Image and Speech Processing • speech emotion recognition • user interfaces and human computer interaction • Voice Analytics
ISBN-10 3-319-27298-5 / 3319272985
ISBN-13 978-3-319-27298-6 / 9783319272986
Zustand Neuware
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