  Given a multi-microphone recording of an unknown number of speakers talking
concurrently, we simultaneously localize the sources and separate the
individual speakers. At the core of our method is a deep network, in the
waveform domain, which isolates sources within an angular region $\theta \pm
w/2$, given an angle of interest $\theta$ and angular window size $w$. By
exponentially decreasing $w$, we can perform a binary search to localize and
separate all sources in logarithmic time. Our algorithm allows for an arbitrary
number of potentially moving speakers at test time, including more speakers
than seen during training. Experiments demonstrate state-of-the-art performance
for both source separation and source localization, particularly in high levels
of background noise.
