Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: New Software and Platforms


Multichannel audio source separation with deep neural networks

Keywords: Audio - Source Separation - Deep learning

Scientific Description: dnnsep is the only source separation software relying on multichannel Wiener filtering based on deep learning. Deep neural networks are used to initialize and reestimate the power spectrum of the sources at every iteration of an expectation-maximization (EM) algorithm. This results in state-of-the-art separation quality for both speech and music.

Functional Description: Combines deep neural networks and multichannel signal processing for speech enhancement and separation of musical recordings.

News Of The Year: In 2017, we changed the type of multichannel filter used and modified the software so that it runs online in real time.