  We investigate which loss functions provide better separations via
benchmarking an extensive set of those for music source separation. To that
end, we first survey the most representative audio source separation losses we
identified, to later consistently benchmark them in a controlled experimental
setup. We also explore using such losses as evaluation metrics, via
cross-correlating them with the results of a subjective test. Based on the
observation that the standard signal-to-distortion ratio metric can be
misleading in some scenarios, we study alternative evaluation metrics based on
the considered losses.
