Music Scene-Adaptive Harmonic Dictionary for Unsupervised Note-Event Detection

Harmonic decompositions are a powerful tool dealing with polyphonic music signals in some potential applications such as music visualization, music transcription and instrument recog- nition. The usefulness of a harmonic decomposition relies on the design of a proper harmonic dictionary. Music scene-adaptive har- monic atoms have been used with this purpose. These atoms are adapted to the musical instruments and to the music scene, in- cluding aspects related with the venue, musician, and other rele- vant acoustic properties. In this paper, an unsupervised process to obtain music scene-adaptive spectral patterns for each MIDI-note is proposed. Furthermore, the obtained harmonic dictionary is ap- plied to note-event detection with matching pursuits. In the case of a music database that only consists of one-instrument signals, promising results (high accuracy and low error rate) have been achieved for note-event detection.

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