metadata

library_name: transformers
base_model: SparkAudio/Spark-TTS-0.5B
tags:
  - text-to-speech
  - tts
  - spark-tts
  - llm-based-tts
  - bambara
  - african-languages
  - open-source
  - mali
  - maliba-ai
  - text-generation-inference
  - transformers
  - unsloth
extra_gated_fields:
  Name: text
  Official Email (organization or academic email): text
  Affiliation (University, Research Lab, etc): text
  I confirm I am a researcher, student, or member of a non-profit organization: checkbox
  I confirm I am NOT affiliated with a for-profit company and will not use this model on behalf of one: checkbox
  I have read and agree to the MALIBA-AI Research License (Non-Commercial, Non-Profit Use Only): checkbox
  I agree to cite the MALIBA-AI paper and all original references when using this model: checkbox
language:
  - bm
language_bcp47:
  - bm-ML
model-index:
  - name: bambara-tts
    results:
      - task:
          name: text-to-speech
          type: speech-synthesis
        metrics:
          - name: Subjective Quality (MOS)
            type: mos
            value: 4.2
          - name: Speaker Similarity
            type: similarity
            value: High
          - name: Naturalness
            type: naturalness
            value: 4.1
pipeline_tag: text-to-speech
license: cc-by-nc-sa-4.0

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.

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

A notebook is available on this link, enabling you to test the model quickly.

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]

License

MALIBA-AI Research Licence - Non-commercial use due to some data used in base model training.

Key Terms

✅ Permitted: research, educational, and personal use
✅ Required: attribution to the original authors
✅ Allowed: derivative works, provided they are shared under the same terms (share-alike)
❌ Prohibited: any commercial use or use by for-profit organizations without obtaining a separate commercial license

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: [email protected]
GitHub: MALIBA-AI
HuggingFace: MALIBA-AI