Improving Impulse Audio Source Separation using Generative Adversarial Networks for Phase Generation

Improving Impulse Audio Source Separation using Generative Adversarial Networks for Phase Generation

This thesis explored separating impulse noise from a desired signal, for the purposes of hearing protection for soldiers and musicians. An evaluation of current techniques in source separation, such as matrix demixing methods (Independent Component Analysis, Independent Vector Analysis), and masking...

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Bibliographic Details
Main Author:	Piercy, Phoebe K.
Other Authors:	Lang, Jeffrey H.
Format:	Thesis
Published:	Massachusetts Institute of Technology 2022
Online Access:	https://hdl.handle.net/1721.1/138956

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