Beyond Artifacts: Towards Generalizable Synthetic Song Detection via Music-Intrinsic Features
The rapid advancement of AI music generators highlights the urgent need for reliable Synthetic Song Detection (SSD). Existing SSD methods often rely on low-level artifacts or fixed feature assumptions, struggling to capture generator-agnostic cues. To address this, we propose Sofia (Synthetic-song detection framework via music features), a flexible framework that models music-intrinsic attributes via feature-specific experts and an adaptive Mixture-of-Experts (MoE) module. By configuring Sofia with representative Vocal, Audio-effect, Global structure features, and their combinations, we present their individual and complementary contributions. To comprehensively evaluate our framework, we...
| Authors | Yan Han, Zhibin Wen, Yuan Wang et al. |
|---|---|
| Primary category | cs.SD |
| Published | 15 June 2026 |
| Last updated at source | 15 June 2026 |
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