Differentiated harmonic feature analysis on music information retrieval for instrument recognition

Abstract

There are lots of different music recommendation systems to help users to get relevant items among the enormous amount of digital music items on all different purposes. The quality of a recommendation system is critically based on what the system can understand about the music objects. This has stimulated the research on automatic music information retrieval. Numerous approaches have been proposed for instrument recognition in terms of feature extraction and selection. Moving Picture Experts Group (MPEG) standardized a set of features based on the digital audio content data for the purpose of interpretation of the information meaning. Features investigated so far are intended to describe a frame window, the whole sound segment, or arbitrarily split bins of the sound segment. Sound vibration in the transient state is known to be significantly different from the one in the quasi-steady state, while information in the transient state is important for instrument recognition by human. However, the boundary of the transient state and feature behaviors in the transient state has been barely investigated. We proposed a differentiated analysis to harmonic features with transient duration boundary detection by instantaneous fundamental frequency in each frame.