Identifying Single Source Data for Mixing Matrix Estimation in Instantaneous Blind Source Separation

Authors:
Pau Bofill
Affiliations:
Dept. d'Arquitectura de Computadors, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain 08036
Venue:
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Year:
2008

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Abstract

This paper presents a simple yet effective way of improving the estimate of the mixing matrix, in instantaneous blind source separation, by using only reliable data.The paper describes how the idea of detecting single source data is implemented by selecting only the data which remain for two consecutive frames in the same spatial signature. Such data, which are most likely to belong to a single source, are then used to accurately identify the spatial directions of the sources and, hence, the mixing matrix.The paper also presents a refined histogram procedure which improves on the potential function method to estimate the mixing matrix, in the two dimensional case (two sensors).The approach was experimentally evaluated and submitted to the first Stereo Audio Source Separation Evaluation Campaign (SASSEC), with good results in matrix estimation both for development and test data.