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Intelligent Audio Source Separation using Independent Component Analysis

The authors introduce the idea of performing it Intelligent ICA to focus on and separate a specific instrument, voice or sound source of interest. This is achieved by incorporating high-level probabilistic priors in the ICA model that characterise each instrument or voice. For instrument modelling, we experimented with various feature sets previously used for instrument or speaker recognition. Prior training of a Gaussian Mixture Model for each instrument was performed. The order of the feature vector, the number of gaussian mixtures and the training audio data length were kept to reasonably minimum levels.

Authors: Mitianoudis, Nikolaos; Davies, Mike
Affiliation: DSP Lab, Queen Mary College, University of London, London, UK
AES Convention:112 (April 2002) Paper Number:5529 Import into BibTeX
Subject:Musical Acoustics

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