How to evaluate TTS for voice agents

Voice-agent text-to-speech should be evaluated beyond naturalness because errors in names, numbers, order codes, prices, and phone numbers can cause major call failures even when a voice sounds high quality. A four-layer approach combines perceived quality through MOS, blind listener preference tests, entity accuracy checks, and production-condition testing, with evaluations using the agent’s actual scripts and 8 kHz telephony audio. The recommended entity test synthesizes realistic sentences, transcribes them using a fixed speech-to-text model without prompts or keyterm hints, normalizes alternative forms of numbers and identifiers, and measures pass rates separately by entity type rather than relying on word error rate. Human review remains necessary for pacing, digit grouping, pronunciation stress, and other usability issues that transcription may miss. Production testing should also assess interruption handling, consistency over long conversations, first-audio latency, and performance at expected concurrency, while continuous testing and observability can detect regressions after provider or model updates.

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