Year: 2013
Type: article
Abstract: We introduce the openSMILE feature extraction toolkit, which unites feature extraction algorithms from the speech processing and the Music Information Retrieval communities.Audio low-level descriptors such as CHROMA and CENS features, loudness, Mel-frequency cepstral coefficients, perceptual linear predictive cepstral coefficients, linear predictive coefficients, line spectral frequencies, fundamental frequency, and formant frequencies are supported.Delta regression and various statistical functionals can be applied to the low-level descriptors.openSMILE is implemented in C++ with no third-party dependencies for the core functionality.It is fast, runs on Unix and Windows platforms, and has a modular, component based architecture which makes extensions via plug-ins easy.It supports on-line incremental processing for all implemented features as well as off-line and batch processing.Numeric compatibility with future versions is ensured by means of unit tests.openSMILE can be downloaded from http://opensmile.sourceforge.net/.
Author: Eyben, F.;Wöllmer, M.;Schuller, B.
Institution: Technical University of Munich
Language: English
Topic: Music and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7073743773