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REPET for Background/Foreground Separation in Audio

Zafar Rafii 1 Antoine Liutkus 2 Bryan Pardo 1
2 PAROLE - Analysis, perception and recognition of speech
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Repetition is a fundamental element in generating and perceiving structure. In audio, mixtures are often composed of structures where a repeating background signal is superimposed with a varying foreground signal (e.g., a singer overlaying varying vocals on a repeating accompaniment or a varying speech signal mixed up with a repeating background noise). On this basis, we present the REpeating Pattern Extraction Technique (REPET), a simple approach for separating the repeating background from the non-repeating foreground in an audio mixture. The basic idea is to find the repeating elements in the mixture, derive the underlying repeating models, and extract the repeating background by comparing the models to the mixture. Unlike other separation approaches, REPET does not depend on special parametrizations, does not rely on complex frameworks, and does not require external information. Because it is only based on repetition, it has the advantage of being simple, fast, blind, and therefore completely and easily automatable.
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https://hal.inria.fr/hal-01025563
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Submitted on : Friday, July 18, 2014 - 9:56:46 AM
Last modification on : Friday, February 26, 2021 - 3:28:06 PM
Long-term archiving on: : Monday, November 24, 2014 - 7:30:54 PM

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Zafar Rafii, Antoine Liutkus, Bryan Pardo. REPET for Background/Foreground Separation in Audio. G.R. Naik and W. Wang. Blind Source Separation, Springer Berlin Heidelberg, pp.395-411, 2014, 978-3-642-55015-7. ⟨10.1007/978-3-642-55016-4_14⟩. ⟨hal-01025563⟩

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