What is Text to Speech?
Also called TTS, Speech Synthesis.
Text to speech is the generation of spoken audio from written text. Neural synthesis models produce speech with natural rhythm and intonation, and can be steered by voice selection, speaking rate, and markup that controls pauses or emphasis. Streaming synthesis begins producing audio before the full text is ready, which matters for live conversation.
Older systems stitched together recorded fragments, which is why they sounded flat at phrase boundaries. Neural systems predict an acoustic representation from text and then render it to a waveform, learning prosody from data. Pronunciation of names, abbreviations, and figures remains the weak spot, so most engines accept phonetic overrides and markup for numbers, dates, and currencies.
For conversational use, the metric that matters is time to first audio rather than total synthesis time. Streaming engines start speaking a sentence while later sentences are still being generated, which hides much of the delay. The tradeoff is that text arriving late can force awkward phrasing, since the opening of the sentence is already spoken and cannot be revised.
Two practical cautions. First, a highly natural voice raises expectations of comprehension, so callers speak more casually and recognition errors increase. Second, synthesized speech that imitates a specific person raises consent and disclosure questions, and several jurisdictions require automated callers to identify themselves. Treat voice choice as a policy decision, not only a design one.
Synthesis is also where written content meets spoken constraints. Text written for the eye, with tables, parentheses, and long clauses, becomes unlistenable when read aloud. Systems that sound good usually generate speech aware text in the first place, with short sentences, front loaded answers, and figures spelled out the way a person would say them.
Key points
- Neural synthesis learns rhythm and intonation from data
- Time to first audio matters more than total synthesis time
- Markup controls pauses, emphasis, numbers, and pronunciation
- Names and abbreviations are the most common mispronunciations
- Text written for reading rarely works when read aloud
In practice
A pharmacy sends prescription ready reminders by phone. The message template inserts the patient's first name, the branch address, and the collection deadline. Without markup, the engine reads the postal code as a single word and the deadline as an ordinal that sounds wrong. Adding pronunciation hints and a short pause before the address makes the whole message intelligible on the first listen.