F5-TTS
Cette page Soniqo documente F5-TTS tel qu'il est implémenté dans speech-swift / speech-core. Les liens Hugging Face sont placés après les notes d'intégration.
Page interne d'abord
Les cartes et menus pointent d'abord ici; les liens vers le modèle source et les bundles restent disponibles sur cette page.
Aperçu
| Modèle | F5-TTS |
|---|---|
| Rôle | Zero-shot voice cloning from a short reference plus transcript |
| Backend | MLX fp16 |
| Sortie | 24 kHz mono waveform |
| Langues | English and Mandarin, mixed EN/ZH supported |
| Licence | CC-BY-NC-4.0 weights; non-commercial bundle |
| État | Ready through speech speak --engine f5 and the F5TTS Swift product |
| Source | SWivid F5-TTS |
| Produit Swift | F5TTS |
| CLI / runtime | speech speak --engine f5 |
Utilisation
L'extrait ci-dessous suit l'API ou la commande actuellement exposée par speech-swift.
# Clone a voice from a ~10 s reference clip plus its transcript.
.build/release/speech speak "Hello from my cloned voice." \
--engine f5 \
--voice-sample reference.wav \
--f5-reference-text "Text spoken in the reference clip." \
-o cloned.wav
Liens du modèle
Notes d'implémentation
- 16 flow steps are the default (RTF 0.57 on an M5 Pro, lower is faster); --f5-steps 32 for maximum fidelity, 12 runs at RTF 0.43 — ASR roundtrips are word-identical across all three.
- --f5-reference-text is required: cloning conditions on the reference transcript, and quality tracks how cleanly the reference clip ends on a sentence boundary.
- Mandarin runs through a bundled pinyin lexicon with tone sandhi baked in at export time (99.2% token-exact against the upstream rjieba/pypinyin frontend), so Swift needs no external tokenizer.
- Deterministic per --f5-seed; --f5-speed scales pacing, CFG strength and sway sampling are exposed as flags; about 0.8 GB peak RSS makes it the smallest cloning engine in the package.