Separation of drums from polyphonic music using non-negative matrix factorization and support vector machine

DMCA

Separation of drums from polyphonic music using non-negative matrix factorization and support vector machine (2005)

Cached

Download Links

by Marko Helén , Tuomas Virtanen

Venue:	In: Proc. EUSIPCO’2005. (2005
Citations:	56 - 4 self

BibTeX

@INPROCEEDINGS{Helén05separationof,
    author = {Marko Helén and Tuomas Virtanen},
    title = {Separation of drums from polyphonic music using non-negative matrix factorization and support vector machine},
    booktitle = {In: Proc. EUSIPCO’2005. (2005},
    year = {2005}
}

OpenURL

Abstract

This paper presents a procedure for the separation of pitched musical instruments and drums from polyphonic music. The method is based on two-stage processing in which the input signal is first separated into elementary time-frequency components which are then organized into sound sources. Non-negative matrix factorization (NMF) is used to separate the input spectrogram into components having a fixed spectrum with time-varying gain. Each component is classified either to pitched instruments or to drums using a support vector machine (SVM). The classifier is trained using example signals from both classes. Simulation experiments were carried out using mixtures generated from real-world polyphonic music signals. The results indicate that the proposed method enables better separation quality than existing methods based on sinusoidal modeling and onset detection. Demonstration signals are available at

Keyphrases

support vector machine polyphonic music non-negative matrix factorization example signal input signal demonstration signal two-stage processing sinusoidal modeling separation quality real-world polyphonic music signal elementary time-frequency component onset detection pitched musical instrument simulation experiment time-varying gain fixed spectrum input spectrogram sound source

DMCA