01In plain English
Text-to-speech turns written words into spoken audio. Modern AI voices can sound close to a real person, with control over accent, pace and emotion, and some can copy a specific voice from a sample.
02How it works
You paste in a script and choose a voice. The software first reads the text and works out how it should sound: which syllables are stressed, how numbers and abbreviations are spoken, and where the pauses fall. Then an AI voice model turns that plan into audio, producing the sound waves one tiny slice at a time so the result flows like a person speaking. Settings let you change the pace, the accent and the mood. Some tools also let you upload a sample of a real voice and clone it. A familiar example is the voice that reads out a train announcement or an audiobook, except you can now generate your own in minutes from a script.
03Why it matters when you are choosing
It is used for voiceovers, audiobooks, support phone lines and making content accessible. Quality, the number of languages and the rights to use the audio vary a lot between tools.
04What to check
Listen to samples in your language, check the commercial use rights for the audio, and check the rules on cloning voices.
05Where you will meet it
06Common questions
Can I use AI voices in a commercial video or podcast?
Often yes, but it depends on the plan. Many tools allow commercial use only on paid tiers, and some restrict resale of the audio itself. Read the license for your plan before you publish, and keep a copy of the terms that applied on the day you made the audio.
What is the difference between text-to-speech and voice cloning?
Text-to-speech uses a ready-made voice from the tool's library. Voice cloning builds a voice that copies a specific person from a recording. Cloning needs the speaker's consent, and good tools require proof of it, because copying a voice without permission can cause legal and ethical trouble.
Why do some AI voices sound robotic?
Older or cheaper voice models read each sentence without understanding the context, so the rhythm and emphasis feel flat. Better models predict how a person would say the line. You can improve results by adding punctuation, spelling out unusual words and breaking long sentences into shorter ones.