Robust TTS Training via Self-Purifying Flow Matching for the WildSpoof 2026 TTS Track

This article describes a research paper focused on improving Text-to-Speech (TTS) models, specifically for the WildSpoof 2026 TTS competition. The core technique involves 'Self-Purifying Flow Matching,' suggesting an approach to enhance the robustness and quality of TTS systems. The use of 'Flow Matching' indicates a generative modeling technique, likely aimed at creating more natural and less easily spoofed speech. The paper's focus on the WildSpoof competition implies a concern for security and the ability of the TTS system to withstand adversarial attacks or attempts at impersonation.