Harmonic-percussive Sound Separation Using Rhythmic Information from Non-negative Matrix Factorization in Single-channel Music Recordings

This paper proposes a novel method for separating harmonic and percussive sounds in single-channel music recordings. Standard non-negative matrix factorization (NMF) is used to obtain the activations of the most representative patterns active in the mixture. The basic idea is to classify automatically those activations that exhibit rhythmic and non-rhythmic patterns. We assume that percussive sounds are modeled by those activations that exhibit a rhythmic pattern. However, harmonic and vocal sounds are modeled by those activations that exhibit a less rhythmic pattern. The classification of the harmonic or percussive NMF activations is performed using a recursive process based on successive correlations applied to the activations. Specifically, promising results are obtained when a sound is classified as percussive through the identification of a set of peaks in the output of the fourth correlation. The reason is because harmonic sounds tend to be represented by one valley in a half-cycle waveform at the output of the fourth correlation. Evaluation shows that the proposed method provides competitive results compared to other reference state-of-the-art methods. Some audio examples are available to illustrate the separation performance of the proposed method.