Performance measurement in blind audio source separation

Emmanuel Vincent 1 Rémi Gribonval 2 Cédric Févotte 3
1 Centre for Digital Music
2 METISS - Speech and sound data modeling and processing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
3 Department of Engineering [Cambridge]
Abstract : In this article, we discuss the evaluation of Blind Audio Source Separation (BASS) algorithms. Depending on the exact application, different distortions can be allowed between an estimated source and the wanted true source. We consider four different sets of such allowed distortions, from time-invariant gains to time-varying filters. In each case we decompose the estimated source into a true source part plus error terms corresponding to interferences, additive noise and algorithmic artifacts. Then we derive a global performance measure using an energy ratio, plus a separate performance measure for each error term. These measures are computed and discussed on the results of several BASS problems with various difficulty levels.
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Emmanuel Vincent, Rémi Gribonval, Cédric Févotte. Performance measurement in blind audio source separation. IEEE Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2006, 14 (4), pp.1462--1469. ⟨inria-00544230⟩

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