Can Whisper AI do text to speech?

No. Whisper does one job in one direction: it takes audio in and writes text out. It cannot read text aloud, and it cannot produce a synthetic voice. People search for both because the two technologies are often discussed together, but they are separate tasks. Text to speech needs a different model, and you choose it for a different reason.

Whisper only recognizes speech, so it cannot speak

OpenAI's Whisper repository describes the model as a general-purpose speech recognition model ¹. Its input is audio, and its output is a transcript. The reverse task, turning written text into audio, is called text to speech, and it uses a different kind of model that generates sound from text.

The confusion is common because a single product often offers both. A voice assistant can listen to you with a recognition model and answer with a speech model. In that case each part does its own job, and the recognition model still cannot speak. The difference is set out in our question on speech to text and text to speech.

OpenAI offers text to speech as a separate endpoint

If you want a voice from OpenAI, the company offers it in a different endpoint from its transcription service. Its text-to-speech guide says the Audio API provides a speech endpoint based on its GPT-4o mini TTS model ². The text-to-speech guide also lets you control aspects of the speech, such as accent, tone and speed of speech, by prompting the model, and its examples save the audio as an MP3 file.

That endpoint is not the Whisper model. Its name, its inputs and its pricing are separate, so a transcription key does not change what the speech endpoint does. Check the current guide before you build, because model names, voices and prices change. Our guide to speech to text APIs compares several providers on both tasks.

Local text to speech runs on your own computer

If you want speech without sending text to a company, a local engine is an option. Home Assistant describes Piper as a fast, local neural text-to-speech system that is optimized for the Raspberry Pi 4 ³. The original Piper repository was archived by its owner on October 6, 2025, and is read-only, with development moved to a successor project ⁴. So check which repository you install, and whether it still receives updates, before you rely on it.

On Windows, the operating system has its own speech interface. Microsoft describes SAPI as an application programming interface that reduces the code an application needs to use both speech recognition and text-to-speech ⁵. An app that uses SAPI can read text aloud through the system's voices, which may suit simple tasks.

It depends on what "voice generator" means to you

The search "Whisper AI voice generator" usually means one of three things, and each has a different answer.

• You want a spoken version of a written script. Use a text-to-speech model or service. Whisper cannot do this, so choose from the TTS options above.
• You want to convert a voice recording into text, then back into a voice. That is a two-step pipeline. Whisper handles the first step, and a speech model handles the second. A speech-to-speech model can also do both in one step.
• You want to clone a voice. Read the terms of any service you use. Voice cloning raises consent and misuse questions, and the sources in this guide do not cover them.

What to do: pick the tool for the output you need

1. Decide the output. If the result is text, Whisper is a candidate. If the result is a voice, you need a speech model.
2. Pick a voice tool and test it on your text. Listen to the output for pronunciation of names, numbers and any unusual words.
3. Check the license and the data terms. For hosted services, confirm what happens to the text you send. For local engines, confirm which project maintains the code.
4. Keep the two steps separate in your plan. A tool that only transcribes will not give you a voice, and a tool that only speaks will not give you a transcript.

For the wider picture of what Whisper does and does not do, read what Whisper AI is. For the term that covers the recognition side, see automatic speech recognition. The overview of speech recognition covers both directions in one place.