  In a scenario with multiple persons talking simultaneously, the spatial
characteristics of the signals are the most distinct feature for extracting the
target signal. In this work, we develop a deep joint spatial-spectral
non-linear filter that can be steered in an arbitrary target direction. For
this we propose a simple and effective conditioning mechanism, which sets the
initial state of the filter's recurrent layers based on the target direction.
We show that this scheme is more effective than the baseline approach and
increases the flexibility of the filter at no performance cost. The resulting
spatially selective non-linear filters can also be used for speech separation
of an arbitrary number of speakers and enable very accurate multi-speaker
localization as we demonstrate in this paper.
