  Within the ambit of VoIP (Voice over Internet Protocol) telecommunications,
the complexities introduced by acoustic transformations merit rigorous
analysis. This research, rooted in the exploration of proprietary sender-side
denoising effects, meticulously evaluates platforms such as Google Meets and
Zoom. The study draws upon the Deep Noise Suppression (DNS) 2020 dataset,
ensuring a structured examination tailored to various denoising settings and
receiver interfaces. A methodological novelty is introduced via Blinder-Oaxaca
decomposition, traditionally an econometric tool, repurposed herein to analyze
acoustic-phonetic perturbations within VoIP systems. To further ground the
implications of these transformations, psychoacoustic metrics, specifically
PESQ and STOI, were used to explain of perceptual quality and intelligibility.
Cumulatively, the insights garnered underscore the intricate landscape of
VoIP-influenced acoustic dynamics. In addition to the primary findings, a
multitude of metrics are reported, extending the research purview. Moreover,
out-of-domain benchmarking for both time and time-frequency domain speech
enhancement models is included, thereby enhancing the depth and applicability
of this inquiry.
