# Waveform Boundary Detection for Partially Spoofed Audio

arXiv: https://arxiv.org/abs/2211.00226 · HTML: https://mlsanity.com/paper/2211.00226/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Nov 2022.

## Built on by (most cited first, 15 of 15)

- [The Age of Synthetic Realities: Challenges and Opportunities](https://mlsanity.com/paper/2306.11503/) (2023)
- [How Do Neural Spoofing Countermeasures Detect Partially Spoofed Audio?](https://mlsanity.com/paper/2406.02483/) (2024)
- [Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook](https://mlsanity.com/paper/2411.19537/) (2024)
- [The defender's perspective on automatic speaker verification: An overview](https://mlsanity.com/paper/2305.12804/) (2023)
- [Coarse-to-Fine Proposal Refinement Framework for Audio Temporal Forgery Detection and Localization](https://mlsanity.com/paper/2407.16554/) (2024)
- [Enhancing Partially Spoofed Audio Localization with Boundary-aware Attention Mechanism](https://mlsanity.com/paper/2407.21611/) (2024)
- [Speech-Forensics: Towards Comprehensive Synthetic Speech Dataset Establishment and Analysis](https://mlsanity.com/paper/2412.09032/) (2024)
- [Analyzing the Impact of Splicing Artifacts in Partially Fake Speech Signals](https://mlsanity.com/paper/2408.13784/) (2024)
- [Toward Robust Real-World Audio Deepfake Detection: Closing the Explainability Gap](https://mlsanity.com/paper/2410.07436/) (2024)
- [Spoof Diarization: "What Spoofed When" in Partially Spoofed Audio](https://mlsanity.com/paper/2406.07816/) (2024)
- [Pindrop it! Audio and Visual Deepfake Countermeasures for Robust Detection and Fine Grained-Localization](https://mlsanity.com/paper/2508.08141/) (2025)
- [The DKU-DUKEECE System for the Manipulation Region Location Task of ADD 2023](https://mlsanity.com/paper/2308.10281/) (2023)
- [NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation](https://mlsanity.com/paper/2509.03829/) (2025)
- [An Unsupervised Domain Adaptation Method for Locating Manipulated Region in partially fake Audio](https://mlsanity.com/paper/2407.08239/) (2024)
- [3-Tracer: A Tri-level Temporal-Aware Framework for Audio Forgery Detection and Localization](https://mlsanity.com/paper/2511.21237/) (2025)

## Abstract (arXiv)

The present paper proposes a waveform boundary detection system for audio spoofing attacks containing partially manipulated segments. Partially spoofed/fake audio, where part of the utterance is replaced, either with synthetic or natural audio clips, has recently been reported as one scenario of audio deepfakes. As deepfakes can be a threat to social security, the detection of such spoofing audio is essential. Accordingly, we propose to address the problem with a deep learning-based frame-level detection system that can detect partially spoofed audio and locate the manipulated pieces. Our proposed method is trained and evaluated on data provided by the ADD2022 Challenge. We evaluate our detection model concerning various acoustic features and network configurations. As a result, our detection system achieves an equal error rate (EER) of 6.58% on the ADD2022 challenge test set, which is the best performance in partially spoofed audio detection systems that can locate manipulated clips.