Synthese vocale neuronale monospeaker francais — FastPitch-Lite + HiFi-GAN (ONNX)
Project description
lectura-tts-monospeaker
Synthese vocale neuronale monospeaker pour le francais.
Installation
# Version minimale (API distante, zero deps)
pip install lectura-tts-monospeaker
# Version locale (inference ONNX)
pip install lectura-tts-monospeaker[onnx]
# Avec G2P integre (texte → audio)
pip install lectura-tts-monospeaker[all]
Utilisation
Depuis du texte (necessite lectura-g2p)
from lectura_tts_monospeaker import synthetiser
audio = synthetiser("Bonjour le monde")
# audio: numpy array float32, 22050 Hz
Depuis des phonemes IPA
from lectura_tts_monospeaker import creer_engine
engine = creer_engine(mode="local")
result = engine.synthesize_phonemes(
"bɔ̃ʒuʁ",
phrase_type=0,
pitch_range=1.3,
)
# result.samples: numpy float32
# result.sample_rate: 22050
# result.phoneme_timings: list[PhonemeTiming]
Via l'API distante
from lectura_tts_monospeaker import creer_engine
engine = creer_engine(mode="api", api_url="https://api.lec-tu-ra.com")
result = engine.synthesize("Bonjour")
Controles prosodiques
| Parametre | Defaut | Description |
|---|---|---|
| duration_scale | 1.0 | Vitesse globale |
| pitch_shift | 0.0 | Decalage F0 (demi-tons) |
| pitch_range | 1.3 | Variation F0 (1.0 = neutre) |
| energy_scale | 1.0 | Intensite |
| pause_scale | 1.0 | Duree des pauses |
| phrase_type | 0 | 0=decl, 1=inter, 2=excl, 3=susp |
Architecture
- FastPitch-Lite : phonemes → mel-spectrogramme (~5M params)
- HiFi-GAN V1 : mel → audio 22050 Hz (~3.5M params)
- Runtime : ONNX (pas de dependance PyTorch)
Licence
Licence proprietaire Lectura. Voir LICENCE.txt.
Project details
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