Weakly Informed Audio Source Separation - Télécom Paris Access content directly
Preprints, Working Papers, ... Year :

Weakly Informed Audio Source Separation

Clément Doire
  • Function : Author
Gael Richard
Roland Badeau

Abstract

Prior information about the target source can improve audio source separation quality but is usually not available with the necessary level of audio alignment. This has limited its usability in the past. We propose a separation model that can nevertheless exploit such weak information for the separation task while aligning it on the mixture as a byproduct using an attention mechanism. We demonstrate the capabilities of the model on a singing voice separation task exploiting artificial side information with different levels of expres-siveness. Moreover, we highlight an issue with the common separation quality assessment procedure regarding parts where targets or predictions are silent and refine a previous contribution for a more complete evaluation.
Fichier principal
Vignette du fichier
WASPAA_paper_2019_HAL.pdf (279.1 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-02332689 , version 1 (25-10-2019)

Identifiers

  • HAL Id : hal-02332689 , version 1

Cite

Kilian Schulze-Forster, Clément Doire, Gael Richard, Roland Badeau. Weakly Informed Audio Source Separation. 2019. ⟨hal-02332689⟩
266 View
363 Download

Share

Gmail Facebook Twitter LinkedIn More