TASU2: Controllable CTC Simulation for Alignment and Low-Resource Adaptation of Speech LLMs
Speech LLM post-training increasingly relies on efficient cross-modal alignment and robust low-resource adaptation, yet collecting large-scale audio-text pairs remains costly. Text-only alignment methods such as TASU reduce this burden by simulating CTC posteriors from transcripts, but they provide limited control over uncertainty and error rate, making curriculum design largely heuristic. We propose \textbf{TASU2}, a controllable CTC simulation framework that simulates CTC posterior distributions under a specified WER range, producing text-derived supervision that better matches the acoustic decoding interface. This enables principled post-training curricula that smoothly vary supervisio...
| Authors | Jing Peng, Chenghao Wang, Yi Yang et al. |
|---|---|
| Primary category | eess.AS |
| Published | 9 April 2026 |
| Last updated at source | 9 April 2026 |
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