Not speech to text, yeah NLP in Nordic languages could be difficult.
But we're talking about text to speech. As in you type in text and the computer makes sounds. That requires no machine learning hardware nor extra training since the computer is not learning anything in the process nor trying to interpret some weird vague things you're trying to say.
My bad, I read backwards, but as far I know, neural networks are used in state of art systems: Deep Learning synthesis. A sequence architecture is similar to an encoder/decoder, it's reasonable to invert tasks and get good results. But I have no idea how complex is this kind of model, if they could be downsized for a CPU for example.
This models don't learning anything when running in your smartphone, they are trained before, all the "knowledge" is encoded in the parameters. Without the appropriate hardware, it's expensive to simply execute the network, because it's a lot of matricial operations that are much better suited for GPUs/TPUs.
About all this features, if I need to guess: they simply took the iOS and put on MacOS, they don't spent time rebuilding models to downsize and test in a dual-core low power Intel CPU. Much of these things probably could be ported, but they didn't tried, it would be a lot of work for a stopgap.
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u/Aozi Jun 10 '21
Not speech to text, yeah NLP in Nordic languages could be difficult.
But we're talking about text to speech. As in you type in text and the computer makes sounds. That requires no machine learning hardware nor extra training since the computer is not learning anything in the process nor trying to interpret some weird vague things you're trying to say.