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Echo-aware signal processing for audio scene analysis: The Call of Echo

Diego Di Carlo 1, 2
1 PANAMA - Parcimonie et Nouveaux Algorithmes pour le Signal et la Modélisation Audio
Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
2 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : Most of audio signal processing methods regard reverberation and in particular acoustic echoes as a nuisance. However, they convey important spatial and semantic information about sound sources and, based on this, recent echo-aware methods have been proposed. In this work, we focus on two directions. First, we study how to estimate acoustic echoes blindly from microphone recordings. Two approaches are proposed, one leveraging on continuous dictionaries, one using recent deep learning techniques. Then, we focus on extending existing methods in audio scene analysis to their echo-aware forms. The Multichannel NMF framework for audio source separation, the SRP-PHAT localization method, and the MVDR beamformer for speech enhancement are all extended to their echo-aware versions.
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https://tel.archives-ouvertes.fr/tel-03133271
Contributor : Diego Di Carlo <>
Submitted on : Monday, February 8, 2021 - 4:57:12 PM
Last modification on : Sunday, March 21, 2021 - 3:06:39 AM

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  • HAL Id : tel-03133271, version 2

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Diego Di Carlo. Echo-aware signal processing for audio scene analysis: The Call of Echo. Signal and Image processing. UNIVERSITÉ DE RENNES 1; INRIA - IRISA - PANAMA, 2020. English. ⟨tel-03133271v2⟩

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