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cs.SD2022★ 1 cited
How to (virtually) train your speaker localizer
Prerak Srivastava, Antoine Deleforge, Archontis Politis +1
Learning-based methods have become ubiquitous in speaker localization. Existing systems rely on simulated training sets for the lack of sufficiently large, diverse and annotated re…
cs.SD2022★ 1 cited
Realistic sources, receivers and walls improve the generalisability of virtually-supervised blind acoustic parameter estimators
Prerak Srivastava, Antoine Deleforge, Emmanuel Vincent
Blind acoustic parameter estimation consists in inferring the acoustic properties of an environment from recordings of unknown sound sources. Recent works in this area have utilize…