AES Europe 2026

The evaluation of audio quality is important in the
development of immersive audio algorithms; reproduction
systems,; binaural models are often used for this as a
quick alternative to listening tests. Coloration (i.e.,
perceived loudness differences integrated across ears;
frequency) is one key quality aspect; however, the majority
of models used to predict coloration are often
oversimplified or are missing a dedicated binaural stage to
consider the relative contribution of the left; right
ear signals. A binaural coloration model is presented that
builds upon previous work; tests three different
approaches for its binaural stage. The proposed model is
evaluated in comparison with nine models that are
frequently used to predict coloration by using data from
five listening tests totaling 252 stimuli with various
audio contents; source positions. The proposed model
performed best with 85% of explained variance, followed by
predictions based on ISO 532-1 loudness, yielding 78%
explained variance. The commonly used log-spectral distance
performed worst, with only 44% explained variance. The
three tested binaural stages had little influence on the
performance of the proposed model. The model is made freely
available to download.