Temporal Constraints for Sound Source Formation using the Normalized Cut

Mathieu Lagrange (1) , Jennifer Murdoch (2) , George Tzanetakis (2)

1 LS2N - Laboratoire des Sciences du Numérique de Nantes
2 UVIC - University of Victoria [Canada]

In this paper, we explore the use of a graph algorithm called the normalized cut in order to organize prominent components of the auditory scene. We focus specifically on defining a time-constrained similarity metric. We show that such a metric can be successfully expressed in terms of the time and frequency masking phenomena and can be used to solve common problems in auditory scene analysis.

Domaines: Machine Learning [stat.ML]; Traitement du signal et de l'image [eess.SP]; Intelligence artificielle [cs.AI]; Apprentissage [cs.LG]; Multimédia [cs.MM]; Traitement du signal et de l'image [eess.SP]

Mathieu Lagrange, Jennifer Murdoch, George Tzanetakis. Temporal Constraints for Sound Source Formation using the Normalized Cut. Neural Information Processing systems (NIPS), workshop on Advances in Models for Acoustic Processing, 2006, Vancouver, Canada. ⟨hal-02005791⟩