Expanding on how Voice Engine works and our safety research. Voice Engine is OpenAI's text-to-speech (TTS) model. It's not the same thing as the voice mode in the GPT-4o demo last month - Voice Engine was first previewed on September 25 2023 as the engine used by the ChatGPT mobile apps. I also used the API version to build my ospeak CLI tool.
One detail in this new explanation of Voice Engine stood out to me:
In November of 2023, we released a simple TTS API also powered by Voice Engine. We chose another limited release where we worked with professional voice actors to create 15-second audio samples to power each of the six preset voices in the API.
This really surprised me. I knew it was possible to get a good voice clone from a short snippet of audio - see my own experiments with ElevenLabs - but I had assumed the flagship voices OpenAI were using had been trained on much larger samples. Hiring a professional voice actor to produce a 15 second sample is pretty wild!
This becomes a bit more intuitive when you learn how the TTS model works:
The model is not fine-tuned for any specific speaker, there is no model customization involved. Instead, it employs a diffusion process, starting with random noise and progressively de-noising it to closely match how the speaker from the 15-second audio sample would articulate the text.
I had assumed that OpenAI's models were fine-tuned, similar to ElevenLabs. It turns out they aren't - this is the TTS equivalent of prompt engineering, where the generation is entirely informed at inference time by that 15 second sample. Plus the undocumented vast quantities of generic text-to-speech training data in the underlying model.
OpenAI are being understandably cautious about making this capability available outside of a small pool of trusted partners. One of their goals is to encourage the following:
Phasing out voice based authentication as a security measure for accessing bank accounts and other sensitive information