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AhmedBensalah8603/Tunisian_TTS

Domain:

natural language processing

Record type:

model
Creator:
Ahm
Host:
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 …

Visit

github.com

Tasks

speech processingtext to speech

Languages

Arabic, Algerian SpokenArabic, Tunisian Spoken

Licenses

Apache-2.0

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