Evaluation of emerging frequency domain convolutive blind source separation algorithms based on real room recordings

Abstract

345-348Additional Information:• This is a conference paper [ c IEEE]. It is also available from: http://ieeexplore.ieee.org/ Personal use of this material is permitted.However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. ABSTRACT This paper presents a comparative study of three of the emerging frequency domain convolutive blind source separation (FDCBSS) techniques i.e. convolutive blind separation of non-stationary sources due to Parra and Spence, penalty function-based joint diagonalization approach for convolutive blind separation of nonstationary sources due to Wang et al. and a geometrically constrained multimodal approach for convolutive blind source separation due to Sanei et al.Objective evaluation is performed on the basis of signal to interference ratio (SIR), performance index (PI) and solution to the permutation problem. The results confirm that a multimodal approach is necessary to properly mitigate the permutation in BSS and ultimately to solve the cocktail party problem. In other words, it is to make BSS semiblind by exploiting prior geometrical information, and thereby providing the framework to find robust solutions for more challenging source separation with moving speakers.Index Terms-Frequency domain (BSS), geometrical constraints, orthogonal/nonorthogonal constraints, penalty functions, cocktail party problem and multimodal signal separation.

A Blind Source Separation Method for Convolved Mixtures by Non-Stationary Vibration Signals

“…The performance of the algorithm on non-stationary block easily is poor. Some of BSS methods for non-stationary signals with convolutive mixtures are sub-band decomposition method in the frequency domain [16][17][18][19]. As the amplitude and the order of signals separated from mixtures are not certain, the method requires additional exact reconstruction process in the whole frequency band [20].…”