  Spatial audio quality is a highly multifaceted concept, with many
interactions between environmental, geometrical, anatomical, psychological, and
contextual considerations. Methods for characterization or evaluation of the
geometrical components of spatial audio quality, however, remain scarce,
despite being perhaps the least subjective aspect of spatial audio quality to
quantify. By considering interchannel time and level differences relative to a
reference signal, it is possible to construct a signal model to isolate some of
the spatial distortion. By using a combination of least-square optimization and
heuristics, we propose a signal decomposition method to isolate the spatial
error from a processed signal, in terms of interchannel gain leakages and
changes in relative delays. This allows the computation of simple energy-ratio
metrics, providing objective measures of spatial and non-spatial signal
qualities, with minimal assumptions and no dataset dependency. Experiments
demonstrate the robustness of the method against common spatial signal
degradation introduced by, e.g., audio compression and music source separation.
Implementation is available at https://github.com/karnwatcharasupat/spauq.
