In Dutch for instance, there's 3 ways to pronounce the R, and everyone has a certain combination of when they use which kind.
In Dutch for instance, there's 3 ways to pronounce the R, and everyone has a certain combination of when they use which kind.
In the US this is highly determined by location, to the point where the New York Times even built a cool quiz [0] that can guess where you're from pretty accurately based on a few dozen vocab questions. So there's a dataset out there that would allow you to handle most of this variance by simply plugging in a ZIP code for the person you're spoofing!
A lot of these generators rely heavily on the base model and are worse at generating e.g. Dutch accented English and/or Dutch accented Dutch. But it works great for e.g. Californian accented English with unique voice.
This learned to be a Shazam for human voices instead of songs. And just like you can figure out by ear a snippet of music was made on a Yamaha DX7, seems 15 seconds is enough to narrow it down to a reasonably small set of vocoders that can recreate the sample given.