Blind Harmonic Adaptive Decomposition applied to supervised source separation

In this paper, a new supervised source separation system is introduced. The Constant-Q Transform (CQT) of an audio signal is first analyzed through an algorithm called Blind Harmonic Adaptive Decomposition (BHAD). This algorithm provides an estimation of the polyphonic pitch content of the input signal, from which the user can select the notes to be extracted. The system then automatically separates the corresponding source from the audio mixture, by means of time-frequency masking of the CQT. The system has been evaluated both in a task of multipitch estimation in order to measure the quality of the decomposition, and in a task of user-guided melody extraction to assess the quality of the separation. The very promising results obtained highlight the reliability of the proposed model.