AI Voice Agent Testing Guide

This guide provides a structured approach to testing AI voice agents, ensuring they perform accurately, efficiently, and reliably in real-world scenarios.

Functional Testing

Speech Recognition (ASR) Accuracy

  • Test different accents, speaking speeds, and background noise.
  • Measure: Word Error Rate (WER), Sentence Error Rate (SER).

Natural Language Understanding (NLU)

  • Validate intent recognition, multi-intent handling, and entity extraction.
  • Measure: Intent Accuracy, F1-score, Confusion Matrix.

Conversational Flow

  • Test interruptions, topic shifts, and fallback responses.
  • Measure: Turn Success Rate, Conversation Completion Rate.

Text-to-Speech (TTS) Quality

  • Evaluate naturalness, pronunciation, and response time.
  • Measure: Mean Opinion Score (MOS), Speech Naturalness Rating.

Performance Testing

Latency Testing

  • Measure response times under different network conditions.
  • Measure: Average Response Time, 95th Percentile Latency.

Load & Stress Testing

  • Simulate concurrent users and peak loads.
  • Measure: Calls Per Second (CPS), System Utilization, Failure Rate.

Robustness Testing

Noise & Environment Handling

  • Test in various background noise conditions.
  • Measure: ASR Accuracy Drop in Noisy Settings.

Adversarial Input Handling

  • Evaluate resilience to incomplete, mixed-language, and inappropriate speech.
  • Measure: False Positive & Negative Rates for handling unexpected inputs.

User Experience (UX) Testing

Human Evaluation

  • Conduct real-user tests and assess clarity and engagement.
  • Measure: NPS, CSAT, Call Completion Rate.

A/B Testing

  • Compare different conversation flows and TTS variations.
  • Measure: User Retention, Engagement Rate.

Continuous Monitoring & Improvement

Real-Time Logging

  • Track ASR errors, failed conversations, and response accuracy.
  • Measure: Errors Per Session, Unresolved Queries.

Feedback & Iteration

  • Collect user feedback to refine AI responses.
  • Measure: Accuracy Gains, Reduction in Fallback Responses.