--- 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 🇲🇱 [![Model architecture](https://img.shields.io/badge/Model_Arch-Spark--TTS-lightgrey)](#model-architecture) | [![Model size](https://img.shields.io/badge/Params-500M-lightgrey)](#model-architecture) | [![Language](https://img.shields.io/badge/Language-bm-lightgrey)](#datasets) | [![License](https://img.shields.io/badge/License-CC--BY--NC--SA--4.0-blue)](#license) ## 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 ```bash pip install git+https://github.com/MALIBA-AI/bambara-tts.git ``` with uv (faster) ```bash 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 ```python 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](https://colab.research.google.com/drive/1rJy-mV4Zte33xOWSpkzmY-jBp0T71AFk?usp=sharing), 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 ml.maliba.ai@gmail.com ## License **[MALIBA-AI Research Licence](https://huggingface.co/MALIBA-AI/bambara-tts/blob/main/LICENCE.md)** - 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 ```bibtex @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](https://maliba-ai.org) - Email: ml.maliba.ai@gmail.com - GitHub: [MALIBA-AI](https://github.com/MALIBA-AI) - HuggingFace: [MALIBA-AI](https://huggingface.co/MALIBA-AI)