Until recently, getting natural-sounding text-to-speech usually meant using a hosted service. If you wanted good quality, you ended up calling an API from Amazon, Microsoft, or Google. That works, but it means relying on a remote service and paying per use for a task that doesn't inherently need to be remote.
There are now models that run fast enough on a regular CPU to be useful in practice. They don't need a GPU, and the audio quality is comparable to what you get from common cloud TTS services. Everything runs locally, without relying on third-party APIs.This aligns well with the expectations of privacy-oriented users.
I wanted to make local, CPU-only text-to-speech conversion usable without requiring people to understand or assemble the underlying tooling, so I built a simple GUI converter that can convert long texts to speech in a matter of minutes.
It supports basic desktop workflows like drag and drop, which makes it more convenient than uploading text to a service and downloading the generated audio files. You can drop in text files, run batch conversions, and get audio files out, all locally.
This is what the main conversion tab looks like while a conversion is running. The focus is on keeping the workflow simple and local: drop text files, process them in batches, and get audio files out without external services.
Here's what the main conversion tab looks like while a conversion is running.
The application is free and runs entirely offline. Project details and downloads are available at https://jimlet.com
This project exists because CPU-only text-to-speech is finally fast enough to be useful. That makes it practical to build local tools that don't rely on cloud APIs or specialized hardware, and to keep them simple and self-contained.
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