Some recent works address the problem of blind source separation with a matrix pencil. In this paper we show that the covariance matrices of the pencil can be computed at the output of a simple linear filter instead of using time-delayed covariance matrices. It is also shown, using block matrix manipulation, that the method might applied when the number of source signals is not equal to the num...

Existing perceptual models of audio quality, such as PEAQ, were designed to measure audio codec performance and are not well suited to evaluation of audio source separation algorithms. The relationship of many other signal quality measures to human perception is not well established. We collected subjective human assessments of distortions encountered when separating audio sources from mixtures...

A general approach introducing priors on the correlation function or equivalently power spectrum of the sources in the Blind Source Separation problem is presented. This prior modifies or constrains the contrast function that measures the independence of the recovered signals depending on its characteristics. Considering the case where the priors correspond to the sources that we are interested...

Abstract. We consider the Blind Source Separation problem of linear mixtures with singular matrices and show that it can be solved if the sources are sufficiently sparse. More generally, we consider the problem of identifying the source matrix S ∈ IR if a linear mixture X = AS is known only, where A ∈ IR, m 6 n and the rank of A is less than m. A sufficient condition for solving this problem is...

Non-negative spectrogram factorization has been proposed for single-channel source separation tasks. These methods operate on the magnitude or power spectrogram of the input mixture and estimate the magnitude or power spectrogram of source components. The usual assumption is that the mixture spectrogram is well approximated by the sum of source components. However, this relationship additionall...

A model for multi-pitch and periodicity analysis of complex audio signals is presented that is more efficient and practical than the Meddis and O’Mard unitary pitch perception model, yet exhibits very similar behavior. In this paper we also demonstrate how to apply this model to source separation of complex audio signals such as polyphonic and multi-instrumental music and mixtures of simultaneo...

This paper introduces the first community-based Signal Separation Evaluation Campaign (SiSEC 2008), coordinated by the authors. This initiative aims to evaluate source separation systems following specifications agreed between the entrants. Four speech and music datasets were contributed, including synthetic mixtures as well as microphone recordings and professional mixtures. The source separat...

In this paper, we present a way to model long-term reverberation effects in under-determined source separation algorithms based on a non-negative decomposition framework. A general model for the sources affected by reverberation is introduced and update rules for the estimation of the parameters are presented. Combined with a wellknown source-filter model for singing voice, an application to th...