Neural Encoding Detection is Not All You Need for Synthetic Speech Detection
Audio and Speech Processing
2026-04-21 v1
Abstract
This paper reviews the current state and emerging trends in synthetic speech detection. It outlines the main data-driven approaches, discusses the advantages and drawbacks of focusing future research solely on neural encoding detection, and offers recommendations for promising research directions. Unlike works that introduce new detection methods or datasets, this paper aims to guide future state-of-the-art research in the field and to highlight the risk of overcommitting to approaches that may not stand the test of time.
Keywords
Cite
@article{arxiv.2604.16700,
title = {Neural Encoding Detection is Not All You Need for Synthetic Speech Detection},
author = {Luca Cuccovillo and Xin Wang and Milica Gerhardt and Patrick Aichroth},
journal= {arXiv preprint arXiv:2604.16700},
year = {2026}
}
Comments
To appear in the proceedings of the IEEE International Workshop on Biometrics and Forensics (IWBF), Sophia Antipolis (France), 2026. Supplementary material available online at: https://neural-isnt-deepfake.github.io/