  Binaural target sound extraction (TSE) aims to extract a desired sound from a
binaural mixture of arbitrary sounds while preserving the spatial cues of the
desired sound. Indeed, for many applications, the target sound signal and its
spatial cues carry important information about the sound source. Binaural TSE
can be realized with a neural network trained to output only the desired sound
given a binaural mixture and an embedding characterizing the desired sound
class as inputs. Conventional TSE systems are trained using signal-level
losses, which measure the difference between the extracted and reference
signals for the left and right channels. In this paper, we propose adding
explicit spatial losses to better preserve the spatial cues of the target
sound. In particular, we explore losses aiming at preserving the interaural
level (ILD), phase (IPD), and time differences (ITD). We show experimentally
that adding such spatial losses, particularly our newly proposed ITD loss,
helps preserve better spatial cues while maintaining the signal-level metrics.
