Separake: Source Separation with a Little Help From Echoes - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year :

Separake: Source Separation with a Little Help From Echoes

Abstract

It is commonly believed that multipath hurts various audio processing algorithms. At odds with this belief, we show that multipath in fact helps sound source separation, even with very simple propagation models. Unlike most existing methods, we neither ignore the room impulse responses, nor we attempt to estimate them fully. We rather assume that we know the positions of a few virtual microphones generated by echoes and we show how this gives us enough spatial diversity to get a performance boost over the anechoic case. We show improvements for two standard algorithms---one that uses only magnitudes of the transfer functions, and one that also uses the phases. Concretely, we show that multichannel non-negative matrix factorization aided with a small number of echoes beats the vanilla variant of the same algorithm, and that with magnitude information only, echoes enable separation where it was previously impossible.
Fichier principal
Vignette du fichier
main.pdf (1.97 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01909531 , version 1 (04-12-2018)

Identifiers

Cite

Robin Scheibler, Diego Di Carlo, Antoine Deleforge, Ivan Dokmanić. Separake: Source Separation with a Little Help From Echoes. ICASSP 2018 - IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2018, Calgary, Canada. pp.6897-6901, ⟨10.1109/ICASSP.2018.8461345⟩. ⟨hal-01909531⟩
204 View
167 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More