Is there any work/progress on a NN/trained model based on Internet Phonetic Alphabet (IPA) transcriptions? I.e. to be able to create an IPA transcription and convert it back to sound.

That approach would be useful for things like shifting a voice to a different accent and to support voices speaking multiple languages.

This can be done to a limited extend for models such as MBROLA voices by mapping the phonemes of one language to the phonemes of the MBROLA voice. MBROLA is more complex in that it supports diphones, and many diphone pairs don't exist, so you need to map 3 phonemes together to get the best matching phonetic transcription.

The IPA approach may also make it better to train the phonetic synthesis, given that the IPA vowels are in a formant continuum (similar to colour wheels and cubes). Then, the model could better learn the variations in voice quality and tambre.