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 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.

Nominated as an outstanding thesis by Technische Universität München, Germany Describes the details and architecture of openSMILE - the number 1 open-source toolkit in speech emotion analytics and computational paralinguistics Reports on extensive automatic classification results for over ten public speech and music databases Includes supplementary material: sn.pub/extras

Inhalt
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.