AIHubSN/Kiriku-Wolof-ASR

Kiriku ASR: Breaking the Silence for Wolof

The largest open-source Automatic Speech Recognition (ASR) model for the Wolof language.

Kiriku-ASR is a state-of-the-art fine-tune of whisper-large-v2. Developed by IA Hub Senegal, this model represents a massive leap forward for West African speech technology.

Why This Matters

Wolof is a low-resource language with zero native support in the original Whisper vocabulary. Kiriku ASR doesn't just fine-tune weights; it expands the model's fundamental understanding:

• Custom Vocabulary: Manually injected Wolof-specific characters (ñ, ë, ŋ, ɗ, ɓ, ƴ) into the tokenizer.
• Smart Initialization: Used "Warm-Starting" from French <|fr|> embeddings to give the model a linguistic head-start.
• Massive Expert Corpus: Trained on 88.27 hours of expert-verified speech—the largest open-source effort for Wolof to date.
• Free-Transcription Mode: Optimized to operate without a forced language token, avoiding the common "hallucination" artifacts found in base models.

Performance & Results

Through rigorous optimization and data augmentation, Kiriku ASR achieves a benchmark-setting Word Error Rate (WER) for the region.

Metric	Score	Note
Best WER	20.70%	New Open Source SOTA for Wolof
Training Data	88.27h	Multi-domain (Agriculture, Banking, Urban)
Base Model	Whisper Large-v2	Enhanced with custom Wolof diacritics

Training Configuration

• Learning Rate: 1e-5 (Cosine schedule)
• Batch Size: 16 (Effective)
• Regularization: Dropout 0.1 to prevent overfitting on low-resource data.
• Augmentation: Gaussian noise, time stretching, and pitch shifting for real-world robustness.

Quick Start

You can start transcribing Wolof immediately using the Hugging Face pipeline API:

from transformers import pipeline
# Load Kiriku ASR
asr = pipeline(
    "automatic-speech-recognition", 
    model="AIHubSN/kiriku-ASR",
    device=0 
)
# Transcribe (Ensure audio is sampled at 16kHz)
result = asr("audio_sample_wolof.wav")
print(result["text"])

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Produced By

This project is a testament to Senegalese AI excellence:

• AI Hub Senegal — Coordination, community mobilization, and project support
• Contact: contact@aihubsenegal.com

Citation

If this work helps your research or application, please cite our efforts:

@misc{iahubsn2026kiriku_asr,
  title        = {Kiriku ASR: Whisper Large-v2 Fine-tuned for Wolof},
  author       = {{IA Hub Senegal},
  year         = {2026},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/AIHubSN/kiriku-ASR}},
  note         = {Fine-tuned on 88.27 hours of expert-verified Wolof speech}
}

Developed with 🤍 in Dakar for the African AI Renaissance.