CICAAR - Convolutive ICA with an Auto-Regressive Inverse Model

Mads Dyrholm, Lars Kai Hansen

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    We invoke an auto-regressive IIR inverse model for convolutive ICA and derive expressions for the likelihood and its gradient. We argue that optimization will give a stable inverse. When there are more sensors than sources the mixing model parameters are estimated in a second step by least squares estimation. We demonstrate the method on synthetic data and finally separate speech and music in a real room recording.
    Original languageEnglish
    Title of host publicationIndependent Component Analysis and Blind Signal Separation
    Publication date2004
    Publication statusPublished - 2004

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