Word Error Rate (WER) is the standard metric used to measure the accuracy of a speech recognition system. It calculates the percentage of word substitutions, deletions, and insertions compared with a correct reference transcript. Lower WER indicates higher transcription accuracy.
Voice AI providers use WER to benchmark speech recognition models, compare ASR systems, evaluate multilingual performance, and continuously improve transcription quality for enterprise applications.