Multi-Channel Source Separation: Overview and Comparison of Mask-based and Linear Separation Algorithms

Separation of speech signals in noisy multi-speaker environments – as exemplified by the cocktail party problem – is a feasible task for a human listener, even under rather severe conditions such as many interfering speakers and loud background noise. Algorithms that help machines perform a similar task are currently the hotbed of research due to their wide range of applications, such as in human-machine interfaces, digital hearing aids, intelligent robots and so on. abStract

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