HRIR Order Reduction using Approximate Factorisation

Claire Masterson, Gavin Kearney, Marcin Gorzel, Frank Boland

Research output: Contribution to journalArticlepeer-review


A factorisation technique is proposed which allows for a direction independent component to be extracted from a set of Head Related Impulse Responses (HRIRs). Each individual HRIR is split into a pair of filters, a direction independent
component which is common to all HRIRs in the dataset and a direction dependent component which is particular to that HRIR. When these are convolved together, the result is a close approximation to the original HRIR. However, different initial conditions for the factorisation algorithm can converge to solutions with drastically different pairs of direction independent and dependent components each of which offer a similarly low reconstruction error. That is, it appears the problem is one with multiple similar local minima. To address the issue of selection of a minimum with psychoacoustic significance the factorisation is refined using a regularisation technique. Two variants of the
regularisation are proposed to provide a more robust algorithm that should be less sensitive to the choice initial condition. One of these is suitable for minimum phase HRIR data and allows for very short direction dependent components to be obtained. The other is suited to initial delay inclusive HRIR data and allows for this initial time delay to be maintained in the direction dependent components. These techniques are applied to HRIR data from
the KEMAR and CIPIC databases and the results show low reconstruction error when the original and reconvolved HRIRs are compared.
Original languageEnglish
Article number6161609
Pages (from-to)1808 - 1817
Number of pages10
JournalIEEE Transactions On Audio Speech And Language Processing
Issue number6
Publication statusPublished - Aug 2012

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