Time-Frequency Consistency Learning for Robust Speech Deepfake Detection
Recently, speech deepfake detection (SDD) has achieved significant progress. However, its robustness evaluation remains largely confined to controlled additive noise scenarios, lacking systematic investigation of the complex distortions introduced by acoustic front-end (AFE) processing pipelines in real-world deployments. In this work, we simulate a unified AFE pipeline comprising acoustic echo cancellation, noise suppression, automatic gain control, and voice activity detection (VAD), and condu
Record details
Published: 20 July 2026
Source: arXiv
Category: Research
Topics: Misinformation · Finance, VC & PE
Retrieved: 21 July 2026
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ethics.ai (20 July 2026), “Time-Frequency Consistency Learning for Robust Speech Deepfake Detection,” evidence record 11983, https://ethics.ai/record/11983 (originally published by arXiv).
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