The trained voice cloning model for my project is 50 megabytes. Anyone with those 50 megabytes can convincingly be me on a phone call.
I did not build the project to prove this point. I built it because every AI voice cloning tool I tried erased my Nigerian accent. ElevenLabs, XTTS, F5-TTS — Western English training data, generic African-accented output. The pipeline that finally worked chains Qwen3-TTS (Alibaba's 1.7B voice cloning model, released January 2026) with a reference clip of my own voice. Runs on free Kaggle GPU. Full write-up at github.com/dannwaneri/naija-voice.
The technical hurdle was small and specific. Qwen3-TTS ships with a hardcoded min_new_tokens=2 at line 2046 of modeling_qwen3_tts.py. The README documents that you can pass Hugging Face generate() kwargs, but this line silently overrides min_new_tokens no matter what you pass. Half the seeds I tried produced mid-sentence truncation because the model was free to emit EOS within a few tokens. Once I patched that line, the pipeline held. Voice consistent across a full minute. Nigerian accent intact.
Issue #55 on the repo has been open since January, filed by a Korean user reporting the same truncation symptom in a different language. Six months, no maintainer response, no root cause identified. I commented with the diagnosis and opened a PR.
