Open-Set Source Tracing as Compositional Factors via Structured Prototypes
Recent research expands beyond binary anti-spoofing with the emergence of Source Tracing, the task of identifying the specific generative origins of synthetic speech. However, current research often equates a "source" with its generative architecture. We propose redefining a source as a compositional tuple of Architecture, Training Data, and other training factors affecting the generated speech. We propose a framework using Structured Orthonormal Prototypes to minimize class overlap and intra-class variance. Our Subspace Partitioning strategy splits the embedding into architecture and data subspaces, while a residual subspace captures stochastic variability, enabling "compositional genera...
| Authors | Santiago Rubio, Antonio Almudévar, Antonio Miguel et al. |
|---|---|
| Primary category | eess.AS |
| Published | 3 July 2026 |
| Last updated at source | 3 July 2026 |
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