Musical Instrument Recognizer "Instrogram" and Its Application to Music Retrieval Based on Instrumentation Similarity

Instrumentation is an important cue in retrieving musical content. Conventional methods for instrument recognition performing notewise require accurate estimation of the onset time and fundamental frequency (FO) for each note, which is not easy in polyphonic music. This paper presents a non-notewise method for instrument recognition in polyphonic musical audio signals. Instead of such note-wise estimation, our method calculates the temporal trajectory of instrument existence probabilities for every FO and visualizes it as a spectrogram-like graphical representation, called an instrogram. This method can avoid the influence by errors of onset detection and FO estimation because it does not use them. We also present methods for MPEG-7-based instrument annotation and music information retrieval based on the similarity between instrograms. Experimental results with realistic music show the average accuracy of 76.2% for the instrument annotation and that the instrogram-based similarity measure represents the actual instrumentation similarity better than an MFCC-based one