Word Error Rate (WER)

Overview

A metric measuring how accurately a voice agent's speech recognition system transcribes spoken words, calculated as errors divided by total words.

Why it matters

If your voice agent consistently misunderstands callers or transcribes names and numbers incorrectly, check WER metrics.

How it works

Word Error Rate (WER) is calculated by measuring the time between specific events in the voice agent pipeline. The measurement starts when the triggering event occurs and ends when the measured outcome is achieved.

Common issues

Organizations implementing Word Error Rate (WER) frequently encounter challenges with measurement accuracy, inconsistent performance across different network conditions, and difficulty achieving target benchmarks. High Word Error Rate (WER) often results from inadequate infrastructure, unoptimized models, or poor network connectivity. Automated testing and monitoring can help identify these issues before they impact production callers.

Implementation guide

Hamming recommends testing WER with 50+ recorded utterances covering diverse accents and background noise conditions. Hamming automatically calculates WER during testing to ensure transcription accuracy meets production standards. Regular WER monitoring helps identify degradation in STT performance before it impacts users.

Hamming's benchmarks

Drawing on Hamming's 10M+ mins protected across 10K+ voice agents:

Learn: Hamming's 5-Factor ASR Evaluation Framework→View all benchmarks→