LeapTalk: Breaking the Latency-Quality Trade-off in Talking Head Generation

LeapTalk introduces a single-step bridge-distillation framework for long-form and real-time talking-head generation. It replaces the conventional noise-to-data formulation with data-to-data transport based on a Brownian bridge, anchored by a persistent reference to reduce identity drift and improve long-term stability. The method also uses an SNR-aligned time transformation to transfer knowledge from a pretrained diffusion teacher to a heterogeneous student model, plus audio-driven classifier-free guidance for lip synchronization. The authors report one-step generation at up to 200 FPS and claim improved efficiency and temporal consistency, although detailed benchmarks are not included in the abstract.