Partially Edited Audio: Generation, Defense, and Open Problems

Recent advances in generative audio models facilitate increasingly flexible and selective editing of linguistic content and paralinguistic, extralinguistic, and other attributes. This paradigm, named partially edited audio, differs from full audio generation as only portions of the real recording are edited. This technique can serve both beneficial and harmful applications. We therefore present a concise survey from both generation and defense perspectives, focusing on audio, as a contribution to the ICASSP 2027 special session entitled "Partially Edited Media: Perspectives from Synthesis and Defense." We first define partially edited audio and argue that what counts as ``fake'' or harmful is an application-dependent judgment, not a fixed property of the edit. We then survey audio editing by editing target, approaches, and evaluation, and then defense methods by detection, localization, diarization, and interpretability, summarizing representative benchmarks and toolkits. Finally, we discuss future directions and open problems.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-27
DOI
https://doi.org/10.48550/arxiv.2610.37640
Primary Topic
Speech Recognition and Synthesis
Type
preprint
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preprint

Partially Edited Audio: Generation, Defense, and Open Problems

David F. Harwath, Sanjeev P. Khudanpur, Siwei Lyu, Nicholas Evans et al.
arXiv (Cornell University)
Speech Recognition and Synthesis
preprint

Partially Edited Audio: Generation, Defense, and Open Problems

David F. Harwath, Sanjeev P. Khudanpur, Siwei Lyu, Nicholas Evans, Abhinav Dhall, Xin Wang, Chengzhe Sun, Lin Zhang, You Zhang, Bowen Shi
preprint en

Abstract

Recent advances in generative audio models facilitate increasingly flexible and selective editing of linguistic content and paralinguistic, extralinguistic, and other attributes. This paradigm, named partially edited audio, differs from full audio generation as only portions of the real recording are edited. This technique can serve both beneficial and harmful applications. We therefore present a concise survey from both generation and defense perspectives, focusing on audio, as a contribution to the ICASSP 2027 special session entitled "Partially Edited Media: Perspectives from Synthesis and Defense." We first define partially edited audio and argue that what counts as ``fake'' or harmful is an application-dependent judgment, not a fixed property of the edit. We then survey audio editing by editing target, approaches, and evaluation, and then defense methods by detection, localization, diarization, and interpretability, summarizing representative benchmarks and toolkits. Finally, we discuss future directions and open problems.

arXiv (Cornell University)
Speech Recognition and Synthesis
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