AhmedBensalah8603/Tunisian_TTS
Domaine:
natural language processingType de record:
model
Créateur:
Ahm
Hôte:
Tunisian dialect speech model fine-tuned on 300 hours of high-quality, authentic Tunisian audio data. Delivers natural and accurate synthesis for Tunisian Darija, capturing unique phonetic nuances, code-switching, and local expressions.
# 🇹🇳 Tunisian_TTS
This is an Arabic text-to-speech (TTS) model fine-tuned on 300 hours of clean Modern Standard Arabic (MSA) audio. It delivers high-quality, natural speech synthesis with full diacritization support and efficient voice cloning from reference audio.
---
## Model Details
- Base Model: SparkAudio/Spark-TTS-0.5B
- Training Data: ~300 hours of clean Arabic audio
- Language: Modern Standard Arabic (MSA)
- Sample Rate: 24kHz
- Tags: speech, arabic, spark, tts, text-to-speech
- License: Fair Non-Commercial Research License
---
## Usage
### Quick Start
You can try the model directly via:
- Colab Notebook: colab.research.google.com
```python
from transformers import AutoProcessor, AutoModel
import soundfile as sf
import torch
# Load model
model_id = "IbrahimSalah/Arabic-TTS-Spark"
device = "cuda" if torch.cuda.is_available() else "cpu"
processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
model = AutoModel.from_pretrained(model_id, trust_remote_code=True).eval().to(device)
# Prepare inputs
inputs = processor(
text="YOUR_TEXT_WITH_TASHKEEL",
prompt_speech_path="path/to/reference.wav",
prompt_text="REFERENCE_TEXT_WITH_TASHKEEL",
return_tensors="pt"
).to(device)
# Generate
with torch.no_grad():
output_ids = model.generate(**inputs, max_new_tokens=8000, temperature=0.8)
# Decode
output = processor.decode(generated_ids=output_ids)
sf.write("output.wav", output["audio"], output["sampling_rate"])
```
## Key Features
- High-quality Arabic speech synthesis with natural prosody
- Efficient voice cloning from reference audio
- Advanced text chunking for long-form content
- Built-in audio post-processing (normalization, silence removal, crossfading)
- Adjustable generation parameters (temperature, top_k, top_p)
---
## Input Requirements
**Important:** Text must include full Arabic diacritization (tashkeel). The model performs poorly on non-diacritized input.
Example of co …