@inproceedings{9bf10338787e4f1292b2173b4e31c04b,
title = "Voice separation with an unknown number of multiple speakers",
abstract = "We present a new method for separating a mixed audio sequence, in which multiple voices speak simultaneously. The new method employs gated neural networks that are trained to separate the voices at multiple processing steps, while maintaining the speaker in each output channel fixed. A different model is trained for every number of possible speakers, and the model with the largest number of speakers is employed to select the actual number of speakers in a given sample. Our method greatly outperforms the current state of the art, which, as we show, is not competitive for more than two speakers.",
author = "Eliya Nachmani and Yossi Adi and Lior Wolf",
note = "Publisher Copyright: {\textcopyright} 2020 37th International Conference on Machine Learning, ICML 2020. All rights reserved.; 37th International Conference on Machine Learning, ICML 2020 ; Conference date: 13-07-2020 Through 18-07-2020",
year = "2020",
language = "الإنجليزيّة",
series = "37th International Conference on Machine Learning, ICML 2020",
pages = "7121--7132",
editor = "Hal Daume and Aarti Singh",
booktitle = "37th International Conference on Machine Learning, ICML 2020",
}