AES Europe 2026

We present Binaspect, an open-source Python library for
binaural audio analysis, visualization,; feature
generation. Binaspect generates interpretable “azimuth
maps” by calculating modified interaural time; level
difference spectrograms,; clustering those
time-frequency (TF) bins into stable time-azimuth histogram
representations. This allows multiple active sources to
appear as distinct azimuthal clusters, while degradations
manifest as broadened, diffused, or shifted distributions.
Crucially, Binaspect operates blindly on audio, requiring
no prior knowledge of head models. These visualizations
enable researchers; engineers to observe how binaural
cues are degraded by codec; renderer design choices,
among other downstream processes. We demonstrate the tool
on bitrate ladders, ambisonic rendering,; VBAP source
positioning, where degradations are clearly revealed. In
addition to their diagnostic value, the proposed
representations can be exported as structured features
suitable for training machine learning models in quality
prediction, spatial audio classification,; other
binaural tasks. Binaspect is released under an open-source
license with full reproducibility scripts at: (link removed
for blind review)