Real-time Speech and Music Classification by Large Audio Feature Space Extraction [electronic resource] /
by Florian Eyben.
- 1st ed. 2016.
- XXXVIII, 298 p. 41 illus., 39 illus. in color. online resource.
- Springer Theses, Recognizing Outstanding Ph.D. Research, 2190-5061 .
- Springer Theses, Recognizing Outstanding Ph.D. Research, .
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.
9783319272993
10.1007/978-3-319-27299-3 doi
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.