AI Voice Clone Accuracy Upgrade

I’m looking for a specialist who can take Aythoos (https://aythoos.cyanorx.com) to the next level by sharpening the core voice-cloning engine. The studio already delivers realistic speech and a smooth web experience; the next milestone is higher fidelity, richer linguistic coverage, and smarter expressiveness.

What I need improved
• Model precision: minimise artifacts and better capture subtle tone shifts so the generated speech feels indistinguishable from the source voice.
• Multilingual capability, emotion-aware output, and a seamless path for users to upload short samples and train their own custom voices.
• Efficient inference that scales—any enhancements must keep latency low and integrate cleanly with the existing Python/TensorFlow back-end and React front-end.

Deliverables
1. Refined cloning model (code + trained checkpoints) meeting measurable quality gains on sample tests.
2. Integrated support for multiple languages, emotion detection, and custom voice training within the current UI/API.
3. Clear setup notes and a short report explaining architecture changes so I can maintain and iterate.

Acceptance criteria
• Side-by-side blind tests show a perceptible quality boost to at least 80 % “real” rating by human listeners.
• Added features run in