Advancements in the Music Information Retrieval Framework AMUSE over the Last Decade

Abstract

AMUSE (Advanced MUSic Explorer) was created 2006 as an open-source Java framework for various music information retrieval tasks like feature extraction, feature processing, classification, and evaluation. In contrast to toolboxes which focus on individual MIR-related algorithms, it is possible with AMUSE, for instance, to extract features with Librosa, process them based on events estimated by MIRtoolbox, classify with WEKA or Keras, and validate the models with own classification performance measures. We present several substantial contributions to AMUSE since its first presentation at ISMIR 2010. They include the annotation editor for single and multiple tracks, the support of multi-label and multi-class classification, and new plugins which operate with Keras, Librosa, and Sonic Annotator. Other integrated methods are the structural complexity processing, chord vector feature, aggregation of features around estimated onset events, and evaluation of time event extractors. Further advancements are a more flexible feature extraction with different parameters like frame sizes, possibility to integrate additional tasks beyond algorithms related to supervised classification, marking of features which can be ignored for a classification task, extension of algorithm parameters with external code (e.g., a structure of a Keras neural net), etc.