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Flow-matching transformers with latent multi-modal conditioning and self-reference can leapfrog existing virtual try-on methods in both visual fidelity and inference speed.
A single system now rivals or beats specialized models across ASR, voice activity detection, language ID, and punctuation, setting a new bar for industrial-grade speech processing.
