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lectura-monospeaker

Moteur de synthese vocale neuronale monospeaker pour le francais — deux modeles au choix : high (Matcha-Conformer) et light (FastPitch) + HiFi-GAN (ONNX).

Installation

# Version minimale (API distante, zero deps)
pip install lectura-monospeaker

# Version locale (inference ONNX)
pip install lectura-monospeaker[onnx]

Pour le pipeline complet texte → audio, utilisez pip install lectura-tts-mono (inclut le G2P).

Utilisation

Depuis des phonemes IPA

from lectura_monospeaker import creer_engine

# Modele high (Conformer, meilleure qualite) — par defaut
engine = creer_engine(mode="local")
result = engine.synthesize_phonemes(
    "bɔ̃ʒuʁ",
    phrase_type=0,
    pitch_range=1.3,
)

# Modele light (FastPitch, plus rapide/leger)
engine_light = creer_engine(mode="local", model="light")
result = engine_light.synthesize_phonemes("bɔ̃ʒuʁ")

Raccourci synthetiser()

from lectura_monospeaker import synthetiser

# High (defaut)
audio = synthetiser("Bonjour le monde.")

# Light
audio = synthetiser("Bonjour le monde.", model="light")

Via l'API distante

from lectura_monospeaker import creer_engine

engine = creer_engine(mode="api", api_url="https://api.lectura.world")
result = engine.synthesize("Bonjour")

Modeles

Modele Architecture Taille (INT8) Qualite Vitesse
high (defaut) Matcha-Conformer + HiFi-GAN ~29 Mo Meilleure ~30x temps-reel
light FastPitch + HiFi-GAN ~28 Mo Bonne ~50x temps-reel

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

  • high : Matcha-Conformer — phonemes → mel-spectrogramme via flow matching ODE
  • light : FastPitch — phonemes → mel-spectrogramme via FFT decoder
  • HiFi-GAN V1 : mel → audio 22050 Hz (partage)
  • Runtime : ONNX (pas de dependance PyTorch)

Emplacements des modeles

Recherche dans l'ordre :

  1. Parametre models_dir explicite
  2. $LECTURA_MODELS_DIR/tts_mono/
  3. ~/.lectura/models/tts_mono/
  4. Modeles embarques dans le package (version privee)

Chaque emplacement peut contenir des sous-repertoires conformer/ et fastpitch/ (nouveau layout) ou les fichiers directement (ancien layout, retrocompatible).

Licence

Code source sous licence AGPL-3.0 — voir LICENCE.txt. Modeles pre-entraines : voir MODEL_LICENCE.md.

Licence commerciale et modeles locaux disponibles — contacter admin@lectura.world.

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