One Missing Word, Two Different Consequences
TL;DR for operators A speech-recognition system can transcribe nearly every word correctly while changing what a customer requests or what a voice assistant is supposed to do. Word Error Rate (WER) cannot distinguish those consequences when the edit counts are identical. SITAR, proposed by Lu and colleagues,1 measures situational distortion: whether transcription errors alter expression, understanding, or intended outcomes. It converts offline contextual judgments into a reusable neural scorer. ...