But they behave just like models which use text tokens internally, which is also pointed out at the end of the above article.
I don't find the articles argument that this is due to tokenisation convincing.
> This is likely because they’re trained on a lot of data generated synthetically with text-to-speech and/or because understanding the tone of the voice (apparently) doesn’t help the models make more accurate predictions.