After listening to the 10-voice comparison MP3 sent on 2026-05-20, the
user picked voices 4 / 6 / 7 as their favourites. They are now first-class
presets alongside F1..F5 / M1..M5 and can be used directly:
wav = pipe.generate("Bonjour", voice="voix_sombre", lang="fr")
wav = pipe.generate("Bonjour", voice="homme_moyen", lang="fr")
wav = pipe.generate("Bonjour", voice="homme_clair", lang="fr")
Blends (created via Pipeline.create_voice with slerp):
voix_sombre F4 60 % + M3 40 % androgyne sombre, velouté et grave
homme_moyen {M1, M2, M3, M4, M5} equal weight masculin standard
homme_clair M1 50 % + M5 50 % masculin brillant, expressif
Same JSON schema as the upstream Supertone presets (style_ttl 1×50×256,
style_dp 1×8×16, both float32, metadata block recording the blend
recipe so the file is self-describing).
MLX-native port of Supertone's Supertonic 3 multilingual TTS. Runs the
full flow-matching + classifier-free-guidance pipeline at ~x100 realtime
on Apple Silicon, with audio cosine 1.0 vs the cached MLX path and
cosine 0.98 vs the upstream ONNX Runtime reference.
Weights are hosted at https://huggingface.co/ambassadia/supertonic-3-mlx
and auto-downloaded on first use; this repository ships the port code,
the model card, audio samples, and a zero-config setup_and_test.sh.
Install:
pip install git+https://gitea.tavportal.com/olivier/supertonic-3-mlx.git
Quick test:
git clone https://gitea.tavportal.com/olivier/supertonic-3-mlx.git
cd supertonic-3-mlx && ./setup_and_test.sh
Licenses (dual): model weights = BigScience Open RAIL-M (Section 4
propagation), port code = Apache-2.0. See LICENSE, LICENSE-CODE, NOTICE.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
