The Perception of Phase Intercept Distortion and its Application in Data Augmentation
Abstract
Phase distortion refers to the alteration of the phase relationships between frequencies in a signal, which can be perceptible. In this paper, we discuss a special case of phase distortion known as phase-intercept distortion, which is created by a frequency-independent phase shift. We hypothesize that, though this form of distortion changes a signal's waveform significantly, the distortion is imperceptible. Human-subject experiment results are reported which are consistent with this hypothesis. Furthermore, we discuss how the imperceptibility of phase-intercept distortion can be useful for machine learning, specifically for data augmentation. We conducted multiple experiments using phase-intercept distortion as a novel approach to data augmentation, and obtained improved results for audio machine learning tasks.
Cite
@article{arxiv.2506.14571,
title = {The Perception of Phase Intercept Distortion and its Application in Data Augmentation},
author = {Venkatakrishnan Vaidyanathapuram Krishnan and Nathaniel Condit-Schultz},
journal= {arXiv preprint arXiv:2506.14571},
year = {2026}
}
Comments
Accepted to the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) 2025. Camera-ready version