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---
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}}
}
``` |