Real-time Speech and Music Classification by Large Audio Feature Space Extraction
Springer International Publishing (Verlag)
978-3-319-80111-7 (ISBN)
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 | 18.06.2018 |
|---|---|
| Reihe/Serie | Springer Theses |
| Zusatzinfo | XXXVIII, 298 p. 41 illus., 39 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 516 g |
| Themenwelt | Informatik ► Software Entwicklung ► User Interfaces (HCI) |
| Technik ► Elektrotechnik / Energietechnik | |
| Schlagworte | Acoustic Feature Extraction • Affective computing • Computational Paralinguistics • Music Information Retrieval • openSMILE • speech emotion recognition • Voice Analytics |
| ISBN-10 | 3-319-80111-2 / 3319801112 |
| ISBN-13 | 978-3-319-80111-7 / 9783319801117 |
| Zustand | Neuware |
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