AES Europe 2026

Perceptual models are playing an important role in
effectively balancing the data compression; fidelity in
audio encoders by leveraging the masking effects in human
auditory perception. For deriving well suitable masking
thresholds, considering tonality is important. In this
study, a novel filter bank is proposed, which uses narrow
complex-valued all-pole gammatone filters followed by a
non-linear spectral spreading processing. With an
appropriate non-linear mapping before spreading,;
inverse non-linear mapping afterwards, differences between
masking strengths of tonal; noise-like maskers can be
directly obtained without explicit tonality estimation.
By employing a suitable non-linearity, level-dependency of
spectral spreading in the human auditory system can also be
modeled. The performance of the proposed approach is
evaluated through subjective listening tests, which include
comparisons with results obtained using partial spectral
flatness measures.