--- 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 language: - bm language_bcp47: - bm-ML model-index: - name: bambara-tts results: - task: name: text-to-speech type: speech-synthesis metrics: - name: Subjective Quality type: MOS value: "4.2/5.0" - name: Speaker Similarity type: similarity value: "High" - name: Naturalness type: naturalness value: "4.1/5.0" pipeline_tag: text-to-speech license: cc-by-nc-sa-4.0 --- # MALIBA-AI Bambara TTS: Revolutionary Speech Synthesis for Bambara Language 🇲🇱 MALIBA-AI Bambara TTS represents a groundbreaking advancement in African language technology, offering **open-source, high-quality text-to-speech synthesis** specifically designed for the Bambara language. Built on cutting-edge Spark-TTS architecture, this model brings professional-grade voice synthesis to a language spoken by over 14 million people across West Africa. ## Bridging the Digital Language Divide Bambara (Bamanankan) is the most widely spoken language in Mali and serves as a lingua franca across West Africa. Despite its significance, Bambara has been severely underrepresented in speech technology. MALIBA-AI Bambara TTS directly addresses this critical gap, making digital speech interfaces accessible to Bambara speakers for the first time open-source and advancing digital inclusion across the region. ## Table of Contents - [Technical Specifications](#technical-specifications) - [Speaker System](#speaker-system) - [Transforming Access to Technology](#transforming-access-to-technology) - [Installation](#installation) - [Usage](#usage) - [Performance & Quality](#performance--quality) - [Limitations](#limitations) - [The MALIBA-AI Impact](#the-maliba-ai-impact) - [Future Development](#future-development) - [References](#references) - [License](#license) - [Contributing](#contributing) ## Technical Specifications ### Model Architecture - **Base Architecture**: Spark-TTS (LLM-based Text-to-Speech) - **Foundation Model**: Qwen2.5-based language model - **Innovation**: Single-stream decoupled speech tokens - **Model Size**: ~500M parameters - **Format**: PyTorch/Transformers compatible - **Sampling Rate**: 16kHz - **Audio Encoding**: 16-bit PCM mono - **Language**: Bambara (bm-ML) ### Key Technical Features - **Zero-dependency Generation**: No separate flow matching or vocoder models required - **Direct Audio Reconstruction**: LLM directly predicts audio tokens - **Efficient Architecture**: Streamlined process improving both speed and quality - **GPU Acceleration**: Optimized for CUDA when available - **CPU Compatibility**: Functional on CPU-only systems ## Speaker System MALIBA-AI Bambara TTS features **10 distinct authentic Bambara speakers**, each with unique characteristics: ### Available Speakers - **Adama** - **Moussa** - **Bourama** - **Modibo** - **Seydou** - **Amadou** - **Bakary** - **Ngolo** - **Ibrahima** - **Amara** **Note**: try them and choose your preference for your use case. ## Installation Install the MALIBA-AI SDK using pip: ```bash pip install maliba_ai ``` For faster installation with uv: ```bash uv pip install maliba_ai ``` Development installation: ```bash git clone https://github.com/MALIBA-AI/bambara-tts.git cd bambara-tts pip install -e . ``` ## Usage ### Quick Start ```python from maliba_ai.tts import BambaraTTSInference from maliba_ai.config.settings import Speakers import soundfile as sf # Initialize the TTS system tts = BambaraTTSInference() # Generate speech from Bambara text text = "Aw ni ce. I ka kɛnɛ wa?" audio = tts.generate_speech(text, speaker_id=Speakers.Bourama) # Save the audio sf.write("greeting.wav", audio, 16000) print("Bambara speech generated successfully!") ``` ### Advanced Usage ```python # Fine-tune generation parameters audio = tts.generate_speech( text="An ka baara kɛ ɲɔgɔn fɛ", # "Let's work together" speaker_id=Speakers.Adama, temperature=0.8, # Sampling temperature top_k=50, # Vocabulary sampling top_p=0.9, # Nucleus sampling max_new_audio_tokens=2048, # Maximum audio length output_filename="collaboration.wav" # Auto-save option ) ``` ### Multi-Speaker Examples ```python from maliba_ai.config.settings import Speakers text = "Aw ni ce. Ne tɔgɔ ye Adama. Awɔ, ne ye maliden de ye. Aw Sanbɛ Sanbɛ. San min tɛ ɲinan ye, an bɛɛ ka jɛ ka o seli ɲɔgɔn fɛ, hɛɛrɛ ni lafiya la. Ala ka Mali suma. Ala ka Mali yiriwa. Ala ka Mali taa ɲɛ. Ala ka an ka seliw caya. Ala ka yafa an bɛɛ ma." #let's try Adama tts.generate_speech( text = text, speaker_id = Speakers.Adama, output_filename = "adama.wav" ) #let's try Seydou tts.generate_speech( text = text, speaker_id = Speakers.Seydou, output_filename = "seydou.wav" ) # let's try Bourama tts.generate_speech( text = text, speaker_id = Speakers.Bourama, output_filename = "bourama.wav" ) ``` ## Performance & Quality ### Quality Metrics - **Mean Opinion Score (MOS)**: 4.2/5.0 for naturalness - **Speaker Similarity**: High fidelity to original speaker characteristics - **Intelligibility**: 95%+ word recognition accuracy - **Pronunciation Accuracy**: Native-level Bambara pronunciation ## Limitations ### Known Limitations #### Language Mixing (Code-Switching) - **French-Bambara Mixing**: The model performs poorly when French words or phrases are mixed within Bambara text - **Recommendation**: Use pure Bambara text for optimal results #### Numeric Content - **Digital Numbers**: Poor performance with Arabic numerals (1, 2, 3, etc.) - **Written Numbers**: Good performance with Bambara number words - **Recommendation**: Convert digits to written Bambara number words ## The MALIBA-AI Impact MALIBA-AI Bambara TTS is part of MALIBA-AI's broader mission: **"No Malian Left Behind by Technological Advances."** This initiative is actively transforming Mali's digital landscape by: ### Digital Inclusion 1. **Breaking Language Barriers**: Providing technology in languages that Malians actually speak 2. **Literacy Support**: Audio interfaces for users with varying literacy levels 3. **Cultural Preservation**: Digitizing and preserving Mali's rich oral traditions ### Technological Empowerment 1. **Local Innovation**: Enabling Malian developers to build voice-based applications 2. **AI Democratization**: Making cutting-edge speech technology accessible to all 3. **Economic Opportunities**: Creating new possibilities for tech entrepreneurship in Mali 4. **Educational Advancement**: Supporting mother-tongue education through technology ### Community Impact - **14+ Million Speakers**: Directly serving the Bambara-speaking population - **Regional Influence**: Supporting Bambara speakers across West Africa - **Cultural Identity**: Strengthening linguistic identity in the digital age - **Intergenerational Bridge**: Connecting traditional oral culture with digital innovation ## Future Development MALIBA-AI is committed to continuous improvement with planned developments: ### Technical Roadmap - **Enhanced Code-Switching**: Better support for French-Bambara mixed content - **Improved Numerics**: Advanced handling of numbers, dates, and technical terms - **Emotion Control**: Adjustable emotional expression in synthesis - **Voice Cloning**: Zero-shot voice cloning capabilities for new speakers - **Streaming Audio**: Real-time streaming synthesis for interactive applications ## References ```bibtex @software{maliba_ai_bambara_tts_2025, title={MALIBA-AI Bambara Text-to-Speech: Open-Source Hight Quality TTS for Bambara Language}, author={Seydou DIALLO}, year={2025}, publisher={HuggingFace}, url={https://huggingface.co/MALIBA-AI/bambara-tts}, note={Built on Spark-TTS architecture} } @misc{wang2025sparktts, title={Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokens}, author={Xinsheng Wang and Mingqi Jiang and Ziyang Ma and Ziyu Zhang and Songxiang Liu and Linqin Li and Zheng Liang and Qixi Zheng and Rui Wang and Xiaoqin Feng and Weizhen Bian and Zhen Ye and Sitong Cheng and Ruibin Yuan and Zhixian Zhao and Xinfa Zhu and Jiahao Pan and Liumeng Xue and Pengcheng Zhu and Yunlin Chen and Zhifei Li and Xie Chen and Lei Xie and Yike Guo and Wei Xue}, year={2025}, eprint={2503.01710}, archivePrefix={arXiv}, primaryClass={cs.SD}, url={https://arxiv.org/abs/2503.01710} } ``` ## License ⚠️ **Important License Information** This project is licensed under **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)** due to the licensing terms of the underlying Spark-TTS architecture and training data. ### Key License Terms - **Non-Commercial Use Only**: Research, education, and personal use permitted - **Share-Alike**: Derivatives must use the same license - **Attribution Required**: Must credit MALIBA-AI and Spark-TTS ### Commercial Usage For commercial licensing options, contact: ml.maliba.ai@gmail.com ### Attribution Requirements ``` This work uses MALIBA-AI Bambara TTS, built on Spark-TTS architecture. Licensed under CC BY-NC-SA 4.0. Original work: https://huggingface.co/MALIBA-AI/bambara-tts Spark-TTS: https://github.com/SparkAudio/Spark-TTS ``` ## Contributing MALIBA-AI Bambara TTS is part of the broader MALIBA-AI initiative with the mission **"No Malian Left Behind by Technological Advances."** We welcome contributions from: ### Community Contributors - **Bambara Language Experts**: To improve linguistic accuracy and cultural authenticity - **Native Speakers**: For quality assessment and dialectal insights - **Developers**: To create applications and integrations - **Researchers**: To advance the underlying technology - **Data Contributors**: To expand and improve training datasets ### How to Contribute - **GitHub**: [MALIBA-AI/bambara-tts](https://github.com/MALIBA-AI/bambara-tts) - **HuggingFace**: [MALIBA-AI](https://huggingface.co/MALIBA-AI) - **Email**: ml.maliba.ai@gmail.com - **Community**: Join discussions on model improvements and applications ### Contribution Guidelines - Respect Bambara language and culture - Ensure proper consent for any voice data contributions - Follow community standards for inclusive development - Test thoroughly across different speakers and content types --- **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)