When the Transcript Stops Being Evidence: Re-Sonance and the Limit of LLM Speech Repair
TL;DR for operators A downstream AI model can rescue imperfect upstream output only while enough evidence survives to reconstruct what was lost. Re-Sonance1 makes that boundary unusually clear: after speech recognition, LLM correction lowers Word Error Rate from 21.58 to 13.74 for mild dysarthria and from 23.70 to 17.88 for moderate dysarthria, but severe-case WER rises from 83.77 to 84.40 and Match Error Rate rises from 87.50 to 90.96. Lower error rates mean the reconstructed wording is closer to the intended transcript. ...