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README.md

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+---
+library_name: transformers
+license: apache-2.0
+language:
+- wo
+base_model:
+- parler-tts/parler-tts-mini-multilingual-v1.1
+pipeline_tag: text-to-speech
+---
+<img src="https://huggingface.co/spaces/CONCREE/Adia_TTS/resolve/main/adia.png" alt=" Adia TTS Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
+
+# Adia_TTS Wolof
+
+<a target="_blank" href="https://huggingface.co/spaces/CONCREE/Adia_TTS">
+  <img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm.svg" alt="Open in HuggingFace"/>
+</a>
+
+# ADIA_TTS : Modèle de synthèse vocale en Wolof
+
+## Table des matières
+1. Introduction
+2. Caractéristiques techniques
+3. Installation
+4. Utilisation
+5. Configuration avancée
+6. Exemples
+7. Limitations
+8. Références
+9. Licence
+
+## Introduction
+ADIA_TTS est un modèle de synthèse vocale (Text-to-Speech) open source en wolof, développé par CONCREE. Basé sur le modèle parler-tts-mini-multilingual-v1.1, il représente une avancée significative dans la synthèse vocale pour la langue wolof.
+
+## Points clés
+* Entraîné sur 40 heures de données vocales en wolof
+* Affiné pendant 100 epochs (~168 heures d'entraînement)
+* Qualité vocale naturelle et fluide
+* Voix unique avec contrôle des caractéristiques vocales via description
+
+
+## Caractéristiques techniques
+
+### Spécifications du modèle
+
+* Architecture : parler-tts-mini-multilingual-v1.1
+* Taille du modèle : 1.88 GB
+* Format du modèle : PyTorch
+* Fréquence d'échantillonnage : 24kHz
+* Encodage audio : 16-bit PCM
+
+### Performance
+
+* Temps moyen d'inférence :  secondes/phrase (CPU), 20 secondes/phrase (GPU)
+* Consommation mémoire : 3.9 GB (RAM minimale recommandée)
+
+## Installation
+### Prérequis
+Python 3.8 ou supérieur
+PyTorch 2.0 ou supérieur
+CUDA (obligatoire, pour accélération GPU)
+```sh
+pip install git+https://github.com/huggingface/parler-tts.git
+```
+
+## Utilisation
+## Exemple de base
+
+```py
+import torch
+from parler_tts import ParlerTTSForConditionalGeneration
+from transformers import AutoTokenizer
+import soundfile as sf
+
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+# Chargement du modèle
+model = ParlerTTSForConditionalGeneration.from_pretrained("CONCREE/Adia_TTS").to(device)
+tokenizer = AutoTokenizer.from_pretrained("CONCREE/Adia_TTS")
+
+# Texte en wolof à synthétiser
+text = "Entreprenariat ci Senegal dafa am solo lool ci yokkuteg koom-koom, di gëna yokk liggéey ak indi gis-gis yu bees ci dëkk bi."
+
+# Description du style vocal
+description = "A clear and educational voice, with a flow adapted to learning"
+
+# Génération
+input_ids = tokenizer(description, return_tensors="pt").input_ids.to(device)
+prompt_ids = tokenizer(text, return_tensors="pt").input_ids.to(device)
+
+audio = model.generate(
+    input_ids=input_ids,
+    prompt_input_ids=prompt_ids,
+)
+
+# Sauvegarde
+sf.write("output.wav", audio.cpu().numpy().squeeze(), model.config.sampling_rate)
+```
+<audio controls>
+  <source src="https://huggingface.co/spaces/CONCREE/Adia_TTS/resolve/main/snt.wav" type="audio/wav">
+</audio>
+
+## Configuration avancée
+## Paramètres de génération
+
+```py
+generation_config = {
+    "temperature": 0.8,           # Contrôle la variabilité de la sortie
+    "max_new_tokens": 1000,       # Longueur maximale de la séquence générée
+    "do_sample": True,            # Active l'échantillonnage aléatoire
+    "top_k": 50,                  # Limite le nombre de tokens considérés
+    "repetition_penalty": 1.2,    # Pénalise la répétition de tokens
+}
+
+audio = model.generate(
+    input_ids=input_ids,
+    prompt_input_ids=prompt_ids,
+    **generation_config
+)
+```
+
+<audio controls>
+  <source src="https://huggingface.co/spaces/CONCREE/Adia_TTS/resolve/main/avct.wav" type="audio/wav">
+</audio>
+
+## Styles vocaux
+### Exemples de descriptions pour différents styles :
+
+1. ### Voix naturelle
+ 
+```py
+description = "A warm and natural voice, with a conversational flow"
+```
+<audio controls>
+  <source src="https://huggingface.co/spaces/CONCREE/Adia_TTS/resolve/main/styl1.wav" type="audio/wav">
+</audio>
+
+2. ### Voix professionnelle
+
+```py
+description = "A professional, clear and composed voice, perfect for formal presentations"
+```
+<audio controls>
+  <source src="https://huggingface.co/spaces/CONCREE/Adia_TTS/resolve/main/styl2.wav" type="audio/wav">
+</audio>
+
+3. ### Voix pour l'éducation
+```py
+description = "A clear and educational voice, with a flow adapted to learning"
+```
+<audio controls>
+  <source src="https://huggingface.co/spaces/CONCREE/Adia_TTS/resolve/main/styl3.wav" type="audio/wav">
+</audio>
+
+## Limitations
+
+* Performance réduite sur les phrases très longues
+* Gestion limitée des nombres et des dates
+* Temps de chargement initial du modèle relativement plus long
+* Le modèle est limité à 200 caractères maximum par inférence sans segmentation. Pour les textes plus longs, une segmentation manuelle est nécessaire.
+* La qualité des transitions entre segments peut varier selon la méthode de segmentation choisie
+* Il est recommandé de segmenter le texte aux frontières naturelles (phrases, paragraphes) pour de meilleurs résultats
+## Références
+
+```
+@misc{CONCREE-2024-Adia_TTS,
+  author = {CONCREE},
+  title = {Adia_TTS},
+  year = {2025},
+  publisher = {Hugging Face},
+  journal = {Hugging Face repository},
+  howpublished = {\url{https://huggingface.co/CONCREE/Adia_TTS}}
+}
+```
+
+```
+@misc{lyth2024natural,
+  title={Natural language guidance of high-fidelity text-to-speech with synthetic annotations},
+  author={Dan Lyth and Simon King},
+  year={2024},
+  eprint={2402.01912},
+  archivePrefix={arXiv},
+  primaryClass={cs.SD}
+}
+```
+
+## Licence
+Ce projet est sous licence Apache 2.0. Voir le fichier LICENSE pour plus de détails.
+
+## Conditions d'utilisation
+
+* Les utilisateurs s'engagent à utiliser le modèle d'une manière qui respecte la langue wolof et la culture sénégalaise.
+* Nous encourageons l'utilisation de ce modèle pour développer des solutions qui améliorent l'accessibilité numérique pour les locuteurs wolof et contribuent à réduire la fracture numérique. Les projets visant l'inclusion numérique sont particulièrement bienvenus.
+* Toute utilisation du modèle doit mentionner CONCREE comme créateur original. Les utilisateurs sont fortement encouragés à partager leurs améliorations avec la communauté.
+* L'utilisation commerciale est autorisée selon les termes de la licence Apache 2.0.
+
+## Contact
+Pour toute question ou support :
+
+Email : ai@concree.com

config.json

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+  "architectures": [
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+  ],
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+    "_name_or_path": "ylacombe/dac_44khz",
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+    "downsampling_ratios": [
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+    "exponential_decay_length_penalty": null,
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+    "id2label": {
+      "0": "LABEL_0",
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+      2
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generation_config.json

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preprocessor_config.json

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special_tokens_map.json

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tokenizer.json

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tokenizer.model

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tokenizer_config.json

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+{
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+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}