WORD ERROR RATE, CHARACTER ERROR RATE, AND PHONEME ERROR RATE IN ASR: WHAT EACH METRIC MEASURES AND WHERE THEY DIVERGE

Word error rate (WER), character error rate (CER), and phoneme error rate (PER) measure different aspects of automatic speech recognition (ASR). Controlled Uzbek examples illustrate how orthographic variation can raise WER without changing PER, while loanwords and allophony can yield higher naive PER than CER. An Acceptance layer distinguishes permissible pronunciation variants from errors. These illustrative findings support complementary evaluation, with explicit documentation of G2P and acceptance criteria rather than population-level conclusions.