Exploiting Melodic smoothness for Melody Detection in Polyphonic audio

This paper describes a method for melody detection in polyphonic musical signals. Our approach starts by obtaining a set of pitch candidates for each time frame, with recourse to an auditory model. Trajectories of the most salient pitches are then constructed. Next, note candidates are obtained by trajectory segmentation (in terms of frequency and pitch salience variations). Too short, low-salience and harmonically-related notes are then eliminated. Finally, the notes comprising the melody are extracted. Comparing to our previous work, we extend it by making use of melodic smoothness for the definition of the final melody notes. We tested our method with excerpts from 21 songs encompassing several genres and obtained an average detection accuracy of 82%. Melody smoothing was responsible for an improvement of 11.8% in the overall accuracy.