10 of Whisper's 70 omissions are not mishearing. The decoder dropped an entity that is in the audio.

I went through the frozen transcripts in predictions/. On 10 of the 240 test files Whisper turbo keeps the framing words and loses the entity. 9 stop right after the lead-in: "Schicken Sie es an", "Ich buchstabiere die Adresse", "Je vous dicte.", "Langsam!". One keeps only the closing "Précisément." Clips run 5.8 to 13.9 s, so this is not a 30 s window cut.

Same master audio, and Voxtral writes the entity on all 10. "Je vous dicte : Fabrice soulignement de la croix verne @example .com". Whisper's own telephone copy of that clip has it too.

So the audio is fine, and tts_alert (both systems far) is right to keep them in. They split 5 clean, 5 telephone, so the channel delta is untouched. Dev adds one more (dev-fr-phone-005, clean), still 0 for Voxtral.

It does change what "omission" means. 10 files is 4.2 pp, bigger than the -2.9 pp Whisper vs Voxtral gap. Voxtral only gets 1 of those 10 right itself, so the gap barely moves. The label does: these are a decoding stop under greedy, not a model that heard nothing.

Would you split early-stop out as its own error class, or rerun Whisper with temperature fallback as a separate row?