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Emmanuel Vincent 1 Tuomas Virtanen 2 Sharon Gannot 3 
1 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : Source separation and speech enhancement research has made dramatic progress in the last 30 years. It is now a mainstream topic in speech and audio processing, with hundreds of papers published every year. Separation and enhancement performance have greatly improved and successful commercial applications are increasingly being deployed. This chapter provides an overview of research and development perspectives in the field. We do not attempt to cover all perspectives currently under discussion in the community. Instead, we focus on five directions in which we believe major progress is still possible: getting the most out of deep learning, exploiting phase relationships across time-frequency bins, improving the estimation accuracy of multichannel parameters, addressing scenarios involving multiple microphone arrays or other sensors, and accelerating industry transfer. These five directions are covered in Sections 19.1, 19.2, 19.3, 19.4, and 19.5, respectively.
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Contributor : Emmanuel Vincent Connect in order to contact the contributor
Submitted on : Tuesday, September 25, 2018 - 9:25:45 PM
Last modification on : Tuesday, October 25, 2022 - 4:22:59 PM
Long-term archiving on: : Wednesday, December 26, 2018 - 5:17:48 PM


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  • HAL Id : hal-01881424, version 1


Emmanuel Vincent, Tuomas Virtanen, Sharon Gannot. Perspectives. Emmanuel Vincent; Tuomas Virtanen; Sharon Gannot. Audio source separation and speech enhancement, Wiley, 2018, 978-1-119-27989-1. ⟨hal-01881424⟩



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