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

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

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.

About This Edition

ISBN: 9783319272986
Publication date:
Author: Florian Eyben
Publisher: Springer an imprint of Springer International Publishing
Format: Hardback
Pagination: 298 pages
Series: Springer Theses
Genres: Electronics engineering
Acoustic and sound engineering
Digital signal processing (DSP)
Human–computer interaction
Computational and corpus linguistics