WER: Word Error Rate (Open ASR Leaderboard)

How It Works

WER is the percent of words in a transcript that differ from the human reference — substitutions, deletions, and insertions all count as one error. It is the canonical accuracy metric for speech-to-text. Lower is better: a WER of 5% means 5 out of every 100 words are wrong.

For each audio clip, the ASR model produces a transcript, which is compared word-for-word to the reference. Errors are summed and divided by the reference length. The Open ASR Leaderboard reports WER averaged across a basket of public datasets to control for dataset-specific quirks.