Multi-scenario deep learning for multi-speaker source separation
2018-08-24Code Available0· sign in to hype
Jeroen Zegers, Hugo Van hamme
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- github.com/JeroenZegers/Nabu-MSSSOfficialIn papertf★ 0
Abstract
Research in deep learning for multi-speaker source separation has received a boost in the last years. However, most studies are restricted to mixtures of a specific number of speakers, called a specific scenario. While some works included experiments for different scenarios, research towards combining data of different scenarios or creating a single model for multiple scenarios have been very rare. In this work it is shown that data of a specific scenario is relevant for solving another scenario. Furthermore, it is concluded that a single model, trained on different scenarios is capable of matching performance of scenario specific models.