Online Score-Informed Source Separation with Adaptive Instrument Models

Abstract

In this paper, an online score-informed source separation system is proposed under the Non-negative Matrix Factorization (NMF) framework, using parametric instrument models. Each instrument is modelled using a multi-excitation source-filter model, which provides the flexibility to model different instruments. The instrument models are initially learned on training excerpts of the same kinds of instruments, and are then adapted, during the separation, to the specific instruments used in the audio being separated. The model adaptation method needs to access the musical score content for each instrument, which is provided by an online audio-score alignment method. Source separation is improved by adapting the instrument models using score alignment. Experiments are performed to evaluate the proposed system and its individual components. Results show that it outperforms a state-of-the-art comparison method.

Keywords:

• NMF
• online
• score-informed
• instrument-models
• adaptive
• score alignment
• source separation

Acknowledgements

We thank the reviewers for their thorough and constructive comments which helped improve the paper significantly.

Notes

1 http://www.jsbchorales.net/index.shtml

Additional information

Funding

This work was supported by the Andalusian Business, Science and Innovation Council under project P2010-TIC-6762 and (FEDER) the Spanish Ministry of Economy and Competitiveness under Project TEC2012-38142-C04-03.