Testing for Diverse Populations

Representative Sample Requirements

Demographic coverage: Include speakers from all major accent groups in your user base Age diversity: Young and elderly speakers (pronunciation varies by generation) Gender representation: Male, female, and non-binary voices Native and non-native: Both native speakers and those with foreign accents Educational background: Varied education levels affect pronunciation

Test Audio Collection

Real-world environments: Record in actual usage scenarios (home, office, mobile) Varied devices: Test across phones, computers, speakerphones, headsets Different networks: WiFi, cellular, landline telephony Time of day: Background noise varies morning vs evening Geographic diversity: Regional accent representation

Accuracy Measurement

Word Error Rate (WER): Percentage of words incorrectly transcribed Sentence Error Rate (SER): Percentage of sentences with any errors Intent accuracy: Whether errors prevent intent understanding (more important than WER) Demographic breakdown: Measure WER separately for each accent group

Target: <10% WER for standard accents, <15% WER for non-standard accents

Continuous Monitoring

Production accuracy tracking: Monitor WER on real calls with consent-based transcription review Accent performance dashboard: Break down accuracy by detected accent/language Degradation alerts: Notify when specific accent groups show accuracy decline Feedback loop: Route low-confidence transcriptions to human review for model improvement