MALIBA-AI Bambara TTS 🇲🇱
Model Overview
This model provides neural text-to-speech synthesis for Bambara (Bamanankan), the most widely spoken language in Mali. The model supports 10 authentic Bambara speakers and produces high-fidelity audio without requiring separate vocoder models. It serves over 14 million Bambara speakers across West Africa with native-level pronunciation and cultural authenticity.
- Available Speakers: Adama, Moussa, Bourama, Modibo, Seydou, Amadou, Bakary, Ngolo, Ibrahima, Amara
⚠️ Non-commercial use only. One of the training data of the base model
spark-ttscarries a license that restricts commercial use.
Quick Start
Installation
pip install git+https://github.com/MALIBA-AI/bambara-tts.git
with uv (faster)
uv pip install git+https://github.com/MALIBA-AI/bambara-tts.git
Note : if you are in colab please install those additional dependencies :
!pip install --no-deps bitsandbytes accelerate xformers==0.0.29.post3 peft trl triton cut_cross_entropy unsloth_zoo
!pip install sentencepiece protobuf huggingface_hub hf_transfer
!pip install --no-deps unsloth
Basic Usage
from maliba_ai.tts.inference import BambaraTTSInference
from maliba_ai.config.settings import Speakers
tts = BambaraTTSInference()
text = "Aw ni ce. I ka kɛnɛ wa?"
audio = tts.generate_speech(text=text, speaker_id=Speakers.Bourama, output_filename="greeting.wav")
Note: More detail : https://github.com/sudoping01/bambara-tts/blob/main/README.md
A notebook is available on this link, enabling you to test the model quickly. The inference server: server
Technical Specifications
Architecture
- Base Model: Spark-TTS (LLM-based TTS)
- Foundation: Qwen2.5-based language model
- Parameters: ~500M
- Audio Format: 16kHz, 16-bit PCM mono
- Language Support: Bambara (bm-ML)
Model Input/Output
Input
- Text: Bambara text in standard orthography
- Speaker ID: Choice of 10 available speakers
- Parameters: Temperature, top-k, top-p (optional)
Output
- Audio: 16kHz mono WAV format
- Quality: Professional-grade speech synthesis
⚠️ Known Limitations
Language Mixing
- Issue: Poor performance with French-Bambara code-switching
- Recommendation: Use pure Bambara text for optimal results
Numeric Content
- Update: We now use Bambara Text Normalizer to preprocess input text. This allows the TTS model to generate speech for digits, dates, and times automatically.
- Integration: This normalization is already built into the MALIBA-AI Bambara TTS Inference framework, so users do not need to manually convert numbers or dates.
- Recommendation: For best results, provide text in standard Bambara orthography, but numeric content and dates are handled automatically.
⚠️ Disclaimer
This model provides high-fidelity Bambara speech synthesis intended for research, education, and community applications. The following uses are strictly forbidden:
- Voice Impersonation: Do not clone voices without explicit consent
- Deceptive Content: Do not generate misleading or fraudulent audio
- Illegal Activities: Do not use for any unlawful purposes
By using this model, you agree to uphold ethical standards and legal responsibilities. We are not responsible for any misuse and firmly oppose unethical usage of this technology.
If you have concerns about potential misuse or need guidance on ethical applications, please contact us at ml.maliba.ai@gmail.com
License
MALIBA-AI Research Licence - Non-commercial use due to some data used in base model training.
Key Terms (Non-Commercial License)
- ✅ Permitted: research, academic, educational, and personal use
- ✅ Required: clear attribution to the original authors (MALIBA-AI)
- ✅ Allowed: modifications and derivative works, provided they are shared under the same non-commercial, share-alike terms
- ❌ Prohibited: any commercial use, monetization, or revenue-generating activity
- ❌ Prohibited: use by companies, startups, or for-profit organizations without prior written permission
- ❌ Prohibited: selling, sublicensing, hosting as a paid service, or integrating into commercial products
If you have any questions, please contact us at: ml[dot]maliba[dot]ai[at]gmail.com
Citation
@software{maliba_ai_bambara_tts,
title={MALIBA-AI Bambara Text-to-Speech: Open-Source High-Quality TTS for Bambara Language},
author={MALIBA-AI},
year={2025},
url={https://huggingface.co/MALIBA-AI/bambara-tts}
}
MALIBA-AI: Empowering Mali's Future Through Community-Driven AI Innovation
"No Malian Language Left Behind"
Contact Information:
- Website: maliba-ai.org
- Email: ml.maliba.ai@gmail.com
- GitHub: MALIBA-AI
- HuggingFace: MALIBA-AI