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Extended nonnegative tensor factorisation models for musical sound source separation.

Derry FitzGerald¹, Matt Cranitch, Eugene Coyle

¹Department of Electronic Engineering, Cork Institute of Technology, Cork, Ireland. derryfitz@eircom.net

Computational Intelligence and Neuroscience

|June 14, 2008

Summary

This study introduces a novel additive synthesis approach for sound source separation, improving musical instrument separation by enabling linear-frequency spectrograms and harmonic constraints. The enhanced model can separate both pitched and percussive instruments together.

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Area of Science:

Music Information Retrieval
Signal Processing
Machine Learning

Background:

Existing shift-invariant tensor factorization algorithms for sound source separation face challenges with log-frequency spectrograms, hindering resynthesis.
Imposing harmonic constraints on recovered basis functions in current models is difficult.

Purpose of the Study:

To propose a new additive synthesis-based approach for sound source separation.
To enable the use of linear-frequency spectrograms and strict harmonic constraints.
To develop an extended model capable of separating mixtures of pitched and percussive instruments.

Main Methods:

Developed a novel additive synthesis-based tensor factorization framework.
Incorporated linear-frequency spectrograms instead of log-frequency spectrograms.
Introduced strict harmonic constraints on the factorisation process.
Integrated a source filter model into the factorization framework.

Main Results:

The proposed method allows for the use of linear-frequency spectrograms, overcoming resynthesis issues.
Strict harmonic constraints improve the factorization model.
The extended model successfully separates mixtures of pitched and percussive instruments simultaneously.

Conclusions:

The new additive synthesis approach offers an improved model for sound source separation.
The ability to use linear-frequency spectrograms and impose harmonic constraints enhances separation quality and resynthesis.
The extended model provides a unified framework for separating diverse musical instrument types.