We've built our own text-to-speech system with an initial English language model we trained ourselves with fully open source data. It will be added to our App Store soon and then included in GrapheneOS as a default enabled TTS backend once some more improvements are made to it.

We're going to build our own speech-to-text implementation to go along with this too. We're starting with an English model for both but we can add other languages which have high quality training data available. English and Mandarin have by far the most training data available.

Existing implementations of text-to-speech and speech-to-text didn't meet our functionality or usability requirements. We want at least very high quality, low latency and robust implementations of both for English included in the OS. It will help make GrapheneOS more accessible.

Our full time developer working on this already built their own Transcribro app for on-device speech-to-text available in the Accrescent app store. For GrapheneOS itself, we want actual open source implementations of these features rather than OpenAI's phony open source though.

Whisper is actually closed source. Open weights is another way of saying permissively licensed closed source. Our implementation of both text-to-speech and speech-to-text will be actual open source which means people can actually fork it and add/change/remove training data, etc.