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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.

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