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Real-time Speech and Music Classification by Large Audio Feature Space Extraction [electronic resource] / by Florian Eyben.

By: Contributor(s): Material type: TextTextSeries: Springer Theses, Recognizing Outstanding Ph.D. ResearchPublisher: Cham : Springer International Publishing : Imprint: Springer, 2016Description: XXXVIII, 298 p. 41 illus., 39 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319272993
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 621.382 23
Online resources:
Contents:
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.
In: Springer eBooksSummary: 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.
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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.

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.