Gaussian framework for interference reduction in live recordings

Diego Di Carlo 1 Ken Déguernel 2, 1 Antoine Liutkus 1
1 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
2 Repmus - Représentations musicales
STMS - Sciences et Technologies de la Musique et du Son
Abstract : In live multitrack recordings, each voice is usually captured by dedicated close microphones. Unfortunately, it is also captured in practice by other microphones intended for other sources, leading to so-called " interferences ". Reducing this interference is desirable because it opens new perspectives for the engineering of live recordings. Hence, it has been the topic of recent research in audio processing. In this paper, we show how a Gaussian probabilistic framework may be set up for obtaining good isolation of the target sources. Doing so, we extend several state-of-the art methods by fixing some heuristic parts of their algorithms. As we show in a perceptual evaluation on real-world multitrack live recordings, the resulting principled techniques yield improved quality.
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  • HAL Id : hal-01515971, version 1

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Diego Di Carlo, Ken Déguernel, Antoine Liutkus. Gaussian framework for interference reduction in live recordings. AES International Conference on Semantic Audio, Jun 2017, Erlangen, Germany. ⟨hal-01515971⟩

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