---
library_name: transformers
base_model: facebook/mms-tts
tags:
- text-to-speech
- vits
- mms
- multilingual
- Open-Source
- Mali
- Bambara
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: "N/A"
pipeline_tag: text-to-speech
license: cc-by-nc-4.0
---

# Bambara TTS

Text-to-speech synthesis model for Bambara (Bamanankan), a language spoken by over 14 million people primarily in Mali.

## Technical Specifications

- **Architecture**: VITS (Variational Inference with adversarial learning for end-to-end TTS)
- **Base Model**: Facebook/Meta MMS
- **Size**: 145 MB
- **Format**: PyTorch 
- **Sampling Rate**: 16kHz
- **Language**: Bambara (bm-ML)
- **Performance**: Optimized for CPU (4GB RAM recommended)

## Installation

```
pip install transformers torch soundfile
```

## Usage

```python
from transformers import VitsModel, AutoTokenizer
import torch

# Load model and tokenizer
model = VitsModel.from_pretrained("sudoping01/bambara-tts")
tokenizer = AutoTokenizer.from_pretrained("sudoping01/bambara-tts")

# Prepare text and generate speech
text = "An filɛ ni ye yɔrɔ minna ni an ye an sigi ka a layɛ yala an bɛ ka baara min kɛ ɛsike a kɛlen don ka Ɲɛ wa ?"
inputs = tokenizer(text, return_tensors="pt")
with torch.no_grad():
    output = model(**inputs).waveform

# Save output
waveform = output.squeeze().cpu().numpy()
sample_rate = model.config.sampling_rate
import soundfile as sf
sf.write("bambara_output.wav", waveform, sample_rate)
```

## Limitations

- Limited handling of loanwords and code-switching with French
- Variable performance across regional dialects
- Requires standard orthography
- Limited prosody and emotional expression

## License

CC BY-NC 4.0 (Attribution-NonCommercial)

- Non-commercial use only
- Attribution required for model authors and Meta
- Use must respect Bambara language and culture

## References

```bibtex
@misc{bambara-tts,
  author = {sudoping01},
  title = {Text-to-Speech Model for Bambara},
  year = {2025},
  publisher = {HuggingFace},
  howpublished = {\url{https://huggingface.co/sudoping01/bambara-tts}}
}
```