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metadata
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

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

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