Yaafe is a low-level and mid-level audio features extractor, designed to extract large number of features over large audio files.
Targeted integrators and users are industrial or academic laboratories in the field of audio signal processing and in particular for music information retrieval tasks.
Yaafe is designed to extract a large number of features simultaneously, in an efficient way. It automatically optimizes features’ computation, so that each intermediate representation (spectrum, CQT, envelope, etc…) is computed only once.
Yaafe works in a streaming mode, so it has a low memory footprint and can process arbitrarily long audio files.
Available features are spectral features, perceptual features (loudness), MFCC, CQT, chroma, chords, onsets detection.
A user can select his own set of features and transformations (derivative, temporal integration), and easily adapt all parameters to his own task.
Yaafe is a C++/Python software available for linux platform (other platform coming soon).
Yaafe will be open-source and released soon under LGPL licence.
Some mid-level features will be available in a separate library, with a proprietary licence.