Text to speech, abbreviated TTS, is technology that converts written text into spoken audio. It covers everything from accessibility screen readers and navigation prompts to the neural voice models creators use for video narration.
The field started with rule based synthesis, moved to concatenative systems that stitched recorded fragments together, and now uses neural models that generate waveforms directly. That last shift is why the flat, clipped voices people associate with the term have largely disappeared, and why synthetic narration is hard to distinguish from a recording in short clips.
Creators encounter TTS in two places. Platform voices built into TikTok and CapCut are recognisable enough to be a stylistic choice in themselves, signalling a format the way a font does. Separately, higher quality external models handle narration for longer scripts where the built in voices become tiring to listen to.
The nuance is that text to speech is the umbrella technology and AI voiceover is one application of it. All AI voiceover is TTS, but plenty of TTS has nothing to do with video: accessibility tools, IVR systems, and reading apps all use it. Treating the terms as synonyms causes confusion when comparing tools, since accessibility engines and creative voice models optimise for different things.
In a video workflow the practical variables are pronunciation control, speed, and consistency across a whole series, which matter more than the raw naturalness of a single test sentence. Names and technical terms are worth checking before a long render, since one mispronounced word repeats across every video in a format.
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