The most interesting thing about this one is the chord progressions it generates.
[0] https://twitter.com/daviddotli/status/1075068713936830464
Edit: to be clear I used to sound male 24/7 and now I sound female 24/7 Rather than thinking you are speaking male or female it helps if you think you are playing a musical instrument with a number of controls that you control (with your mind whahahaha). Then it is just about learning what each control does and how to play them so you get the result you want.
Your voice is muscle memory so while at the start I had to actively "play" a female voice that is no longer the case and now if I ever want to "play" a male voice I have to actively think about how I am going to speak each word to make it male.
In addition, this would imply that only males can talk in a low register, which is patently false. Low register female voices are fairly common.
[1] https://www.urbandictionary.com/define.php?term=pink%20tromb...
"69 adj. Large quantity. Usage: Exclusive to MIT-AI. "Go away, I have 69 things to do to DDT before worrying about fixing the bug in the phase of the moon output routine..." (Note: Actually, any number less than 100 but large enough to have no obvious magic properties will be recognized as a "large number". There is no denying that "69" is the local favorite. I don't know whether its origins are related to the obscene interpretation, but I do know that 69 decimal = 105 octal, and 69 hexadecimal = 105 decimal, which is a nice property. - GLS)"
I'd also (as an English speaker) like to see/hear Dutch g and Xhosan clicks.
specifically: https://twitter.com/shaunlebron/status/989192507828432896
[1] https://de.wikipedia.org/wiki/Wolfgang_von_Kempelen#Die_Spre...
Code's here if anyone wants to play: https://stackblitz.com/edit/ohgodwhathaveidone – I did a fairly medium job of abstracting the synthesis engine away from the UI, but it might be a decent starting point if you're looking to make other Trombone-based web silliness.
Literate depot: https://github.com/PaulBatchelor/voc
Actually compiled source is there: https://github.com/PaulBatchelor/Soundpipe/blob/master/modul...
https://www.speex.org/docs/manual/speex-manual/node9.html
Bitrate comparison:
https://www.speex.org/comparison/
Samples:
https://www.speex.org/samples/
Maybe higher compression can be achieved with better prediction, aka machine learning.
https://www.youtube.com/watch?v=PDn7ygnJUfI
https://www.youtube.com/watch?v=3jcqKnIa8T4
... which is because the latter was patterned after the shape of the mouth.
