Text-to-speech is the technology that converts written text into spoken audio output. TTS is the final step in the voice AI pipeline, transforming AI-generated responses into speech that callers hear.
How does TTS work?
Neural TTS models trained on human speech recordings learn to generate natural-sounding audio from text. They handle pronunciation, intonation, pacing, and emotional expression. SSML markup can provide additional control over emphasis, pauses, and speaking style.
Why does TTS matter?
TTS quality directly impacts caller experience. Natural, expressive speech sounds professional and builds trust. Robotic or awkward speech undermines confidence in the system. Low-latency TTS is also critical since slow synthesis delays responses and disrupts conversation flow.
TTS in practice
An AI agent needs to convey bad news about a canceled appointment. The TTS renders the response with appropriate tone, slightly slower pace and softer intonation that conveys empathy. The same text delivered with an upbeat tone would feel inappropriate. Proper TTS expression matches the emotional context of the message.