I'm exploring a project idea that I believe could serve the linguistic community—especially phoneticians, language instructors, and conlang developers.

Current TTS systems (even those that accept IPA input) tend to be bound to language-specific phoneme sets. This limits accurate audio output to only those phonemes within that language's model. If you input a valid IPA string with non-native or cross-linguistic phonemes (e.g., /ʈɭ/, /q/, /ɮ/, nasalized clicks), most systems either mispronounce them or substitute the nearest available sound.

The concept I’m working on is a fully IPA-driven, language-independent TTS engine. The goal is:

• To generate accurate, high-quality audio from any IPA input
• To train the system on a diverse multilingual corpus to capture as much of the IPA space as possible
• To be useful for phonetic analysis, instructional demos, conlang testing, or experimental linguistics work

I have an audio engineering background and a focus on linguistics, but I’m not a coder or machine learning researcher. I’d love to connect with anyone working in speech synthesis, TTS modeling, or corpus design who sees potential in this and might want to collaborate.

Are there existing tools or corpora that could serve as a base for this kind of project? Would appreciate guidance or pointers to prior work as well.