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arXiv · 1910.10242

Algorithm for Independent Vector Extraction Based on Semi-Time-Variant Mixing Model

Zbyněk Koldovský·Václav Kautský·Tomáš Kounovský·Jaroslav Čmejla
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Abstract

A new algorithm for dynamic independent vector extraction is proposed. It is based on the mixing model where mixing parameters related to the source-of-interest (SOI) are time-variant while the separating parameters are time-invariant. A contrast function based on the quasi-likelihood approach is optimized using the Newton-Raphson approach. The update is computed without imposing the orthogonal constraint, and the orthogonality is enforced afterward. This yields an algorithm that is significantly faster than gradient-based algorithms while different from fixed-point methods, which are even faster. We show advantageous properties of the proposed algorithm compared to the fixed-point methods in an on-line processing regime where stable convergence to the SOI is the important issue. The effectiveness of the method is demonstrated in a speech extraction experiment with a dense microphone array.

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Zbyněk Koldovský, Václav Kautský, Tomáš Kounovský, Jaroslav Čmejla. 2021-03-01. Algorithm for Independent Vector Extraction Based on Semi-Time-Variant Mixing Model. https://arxiv.org/abs/1910.10242

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