This work proposes a melody extraction method which combines a pitch salience function based on source-filter modelling with melody tracking based on pitch contour selection. We model the spectrogram of a musical audio signal as the sum of the leading voice and accompaniment. The leading voice is modelled with a Smoothed Instantaneous Mixture Model (SIMM), and the accompaniment is modelled with a Non-negative Matrix Factorization (NMF). The main benefit of this representation is that it incorporates timbre information, and that the leading voice is enhanced, even without an explicit separation from the rest of the signal. Two different salience functions based on SIMM are proposed, in order to adapt the output of such model to the pitch contour based tracking. Candidate melody pitch contours are then created by grouping pitch sequences, using auditory streaming cues. Finally, melody pitch contours are selected using a set of heuristic rules based on contour characteristics and smoothness constraints. The evaluation on a large set of challenging polyphonic music material, shows that the proposed salience functions help increasing the salience of melody pitches in comparison to similar methods. The complete melody extraction methods also achieve a higher overall accuracy than state-of-the-art approaches when evaluated on both vocal and instrumental music.

This work is partially supported by the European Union under the PHENICX project (FP7-ICT-601166) and the Spanish Ministry of Economy and Competitiveness under CASAS project (TIN2015-70816-R) and Maria de Maeztu Units of Excellence Programme (MDM-2015-0502).