Call transcription accuracy benchmarks: What contact centers should measure

Call transcription accuracy is crucial for contact centers, yet public Speech-to-Text (STT) benchmarks often fail to reflect real-world performance due to their reliance on clean, English audio, which contrasts sharply with the diverse and noisy environments of actual contact center calls. To properly evaluate STT vendors, it's essential to measure metrics such as Word Error Rate (WER) overall and per language and accent, Diarization Error Rate (DER), latency percentiles (p50, p95, p99), and code-switching accuracy using the contact center's own production audio. Self-reported accuracy claims are unreliable without transparent methodologies, and hidden costs for features like diarization and Named Entity Recognition (NER) can accumulate significantly. A successful evaluation requires a comprehensive testing methodology that includes diverse acoustic conditions, languages, speaker demographics, and difficulty tiers to accurately predict production performance and economic viability. The guide emphasizes the importance of establishing standardized transcription benchmarks tailored to the specific needs and conditions of contact centers to avoid flawed analytics and the propagation of errors through downstream systems.

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