How human feedback actually steers TTS fine-tuning

Notes on the iteration loop we ran while fine-tuning F5-TTS and StyleTTS2 on

a small Northern English corpus. The headline finding is that the listening

test isn't optional polish at the end — it's the only measurement that

catches the failure modes that matter, and each round of listening produces

specific phonetic observations that map to specific engineering decisions.

This is a write-up of the methodology, with the concrete examples that

forced each decision.

The loop

┌────────────────────────┐ │ render passage │ │ (baseline + ft) │ └──────────┬─────────────┘ ▼ ┌────────────────────────┐ a feature is "right" if a native │ human listens against │ speaker recognises it. Record both │ marker list (BATH, │ ◀───── what's working AND what's broken; │ FOOT-STRUT, …) │ both are signal. └──────────┬─────────────┘ ▼ ┌────────────────────────┐ translate audible features │ diagnose: why is the │ to training-side cause: │ output the way it is?…