Real-time Speech and Music Classification by Large Audio Feature Space Extraction (Springer Theses)

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.