In a paper published on the preprint server Arxiv.org, researchers at Google and the University of Illinois propose mixture invariant training (MixIT), an unsupervised approach to separating, isolating, and enhancing the voices of multiple speakers in an audio recording. This approach requires only single-channel (e.g., monaural) acoustic features, and researchers claim it “significantly” improves speech