MALIBA-AI/bambara-tts

MALIBA-AI Bambara TTS 🇲🇱

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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.

• Try our live demo on Hugging Face Spaces
• Available Speakers: Adama, Moussa, Bourama, Modibo, Seydou, Amadou, Bakary, Ngolo, Ibrahima, Amara

Quick Start

Installation

  pip install maliba-ai==1.1.1b0

For development installations:

pip install git+https://github.com/MALIBA-AI/bambara-tts.git

with uv (faster)

    uv pip install maliba-ai==1.1.1b0

    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_path="greeting.wav")

Note: More detail : https://github.com/sudoping01/bambara-tts/blob/main/README.md

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

• Issue: Suboptimal handling of Arabic numerals (1, 2, 3...)
• Recommendation: Convert numbers to written Bambara words

⚠️ 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 [email protected]

Impact & Mission

Part of MALIBA-AI's mission: "No Malian Left Behind by Technological Advances"

• 14+ Million Speakers: Serving Bambara speakers across West Africa
• Digital Inclusion: Breaking language barriers in technology
• Cultural Preservation: Supporting Mali's linguistic heritage
• Community Empowerment: Enabling local innovation and development

License

CC BY-NC-SA 4.0 - Non-commercial use only due to Spark-TTS base model licensing.

Key Terms

• ✅ Research, education, and personal use
• ✅ Attribution required
• ✅ Share-alike derivatives
• ❌ Commercial use without license

For commercial licensing: [email protected]

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}
}

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MALIBA-AI: Empowering Mali's Future Through Community-Driven AI Innovation

"No Malian Language Left Behind"

Contact Information:

• Website: maliba-ai.org
• Email: [email protected]
• GitHub: MALIBA-AI
• HuggingFace: MALIBA-AI