Multi-scenario deep learning for multi-speaker source separation

© 2018 IEEE. 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.

ISBN:9781538646588

Jaar van publicatie:2018

BOF-keylabel:ja

IOF-keylabel:ja

Authors from:Higher Education

Toegankelijkheid:Open