WER is a pretty strict metric. IIRC it can penalize missing repeats, disfluencies, and the like that an ASR model may reasonably decide to drop. Additionally it

WER is a pretty strict metric. IIRC it can penalize missing repeats, disfluencies, and the like that an ASR model may reasonably decide to drop. Additionally it will penalize for incorrect pluralization, unique proper nouns that aren't in the model, etc. 10% is still very readable. I built a tool in the mid-201Xs on an ASR engine with 20%+ WER, and even that was good enough for what we were trying to do.