AES Europe 2026

Accurate identification of audio coding artifacts is
instrumental in encoder design, audio post-processing,;
perceptual quality assessment. This paper addresses the
detection of artifacts arising from changes in the
effective bandwidth of coded audio signals caused by coarse
spectral quantization. Such bandwidth variations give rise
to two prominent artifact types: bandwidth limitation (BL)
; birdies, also referred to as spectral islands (SI).
Blind detection methods, requiring no reference signal, are
presented for both artifact types. Bandwidth limitation
is detected by analyzing variations in the zero-crossing
count across time-domain subband signals, enabling
estimation of both fixed; time-varying cutoff
frequencies. Spectral islands are identified through
analysis of the spectrogram by detecting clusters of
isolated components in the time–frequency domain,
characterized by their temporal; spectral extents. The
proposed methods are evaluated using audio material from
the ODAQ; USAC verification datasets. Results show that
the BL detection method achieves an average bandwidth
estimation error of approximately 160 Hz; demonstrates
robustness to noisy bandwidth-limited signals. In addition,
the detected birdie artifacts are perceptually validated
through listening tests, indicating an improvement in
perceived quality following detection; subsequent
suppression of the birdie artifacts.