WER

Speech recognition accuracy and deployment Accuracy in speech recognition matters for user trust and task success. In practice, teams use Word Error Rate (WER) as a key metric—the share of words that are incorrect, missed, or added in a transcript. A lower WER usually means a better user experience, but real applications must balance accuracy with latency, privacy, and cost. What drives WER? The acoustic model converts sound to sounds-like units, while the language model helps select the right words given context. If your app focuses on a niche domain, such as medical notes or travel itineraries, domain coverage matters a lot. Noise, room reverberation, and the quality of the microphone also push WER up. Small changes in sampling rate or text preprocessing can ripple into the final transcription. ...