Voice spoofing detection corpus for single and multi-order audio replays
Open accessIntegrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The semantic approach by Baumann et al. shows robustness in cross-dataset scenarios.
“This semantic approach shows robustness in cross-dataset scenarios.”
From Deepfake forensics: a survey of digital forensic methods for multimodal deepfake identification on social media (2024) · cites this paper as Baumann et al. (2021)
The citation lists haven’t been fetched yet
References 19 · Cited by 36
- Authors
- Baumann, R., Malik, K. M., Javed, A., Ball, A., Kujawa, B., & Malik, H.
- Affiliations
- Oakland University (US)
- University of Michigan–Dearborn (US)
- Corresponding author
- Malik, Khalid Mahmood
- Venue
- Computer Speech & Language
- Publisher
- Elsevier BV
- Published
- 2021-01
- Volume
- 65
- Pages
- 101132
- ISSN
- 0885-2308 (ISSN-L)
- OpenAlex
- W2972017669
- Cited by
- 36
- References
- 19
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 11 · 2023: 6 · 2022: 7 · 2021: 4 · 2020: 1
- FWCI
- 1.74
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Computer Speech & Language (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Science Foundation
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Physical Sciences › Computer Science › Signal Processing › Biometric Identification and Security
- Physical Sciences › Computer Science › Signal Processing › Speech and Audio Processing
- Keywords
- voice spoofing detection, replay attacks, voice-controlled devices, microphone array, speaker verification, Internet of Things security
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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