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Voice Separation with an Unknown Number of Multiple Speakers

2020-02-29ICML 2020Code Available2· sign in to hype

Eliya Nachmani, Yossi Adi, Lior Wolf

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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.

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Benchmark Results

DatasetModelMetricClaimedVerifiedStatus
WHAMR!VSUNOSSI-SDRi12.2Unverified
WSJ0-2mixGated DualPathRNNSI-SDRi20.12Unverified
WSJ0-3mixGated DualPathRNNSI-SDRi16.85Unverified
WSJ0-4mixGated DualPathRNNSI-SDRi12.88Unverified
WSJ0-5mixGated DualPathRNNSI-SDRi10.56Unverified

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