Instrumentation analysis and identification of polyphonic music using beat-synchronous feature integration and fuzzy clustering

In this paper, a music instrumentation analysis and identification method is proposed. In contrast to existing systems, it tries to identify the whole instrument set in polyphonic music and also decide whether each instrument actually dominates at a particular moment or not, but without calculating the exact pitch, onset timing, or the volume of each note. Moreover, it does not require the music source separation in advance. We address this problem by incorporating the beatsynchronous scheme with fuzzy clustering to analyze the instrument components. Experiments show that the instrument identification process results in an 85.19% averaging recognition rate, which is comparable with other existing systems. In addition, it generates the extra time-varying instrumentation information. This information can be considered as a new mid-level feature in music information retrieval systems.