hundehanna/amharic-asr
Domaine:
natural language processingType de record:
model
Créateur:
hun
Hôte:
Fine-tuned OpenAI Whisper-medium on the Leyu Amharic dataset (4 dialects, ~27k samples) for Automatic Speech Recognition. Includes Colab training notebook and Gradio demo.
# Amharic Speech Recognition — Fine-tuned Whisper Medium
Fine-tuned `openai/whisper-medium` on the Leyu Amharic dataset — a multi-dialect Amharic speech corpus covering Gojjam, Gonder, Wello, and Shewa dialects (~27,000 samples). This project demonstrates end-to-end low-resource ASR development for Amharic (አማርኛ), one of Ethiopia's most widely spoken languages.
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## Live Demo
> Try the model directly in your browser — no setup required.
**🎙️ Launch Demo on HuggingFace Spaces**
Record your voice or upload an audio file to receive an Amharic transcript.
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## Results
| Model | WER ↓ | Notes |
|-------|--------|-------|
| `openai/whisper-medium` (zero-shot baseline) | _TBD_ | No fine-tuning |
| `whisper-medium-amharic` (this model) | _TBD_ | Fine-tuned on Leyu |
> Results will be updated after training completes.
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## Dataset: Leyu Amharic
| Dialect | HuggingFace ID | Samples | Duration |
|---------|----------------|---------|----------|
| Gojjam | `leyu-amharic/leyu-amharic-gojjam-dialect` | 10,575 | 81.6h |
| Gonder | `leyu-amharic/leyu-amharic-gonder-dialect` | 8,990 | — |
| Wello | `leyu-amharic/leyu-amharic-wello-dialect` | 4,860 | — |
| Shewa | `leyu-amharic/leyu-amharic-shewa-dialect` | 2,590 | — |
| **Total** | | **~27,000** | |
- Audio: `.wav`, 16kHz mono
- Transcripts: Ethiopic script (`text` column)
- Speakers: mixed gender, recorded on mobile devices in real environments
- All datasets only ship with a `train` split — we apply an 80/10/10 train/val/test split
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## Model
- **Base**: `openai/whisper-medium` (307M parameters)
- **Task**: Automatic Speech Recognition (`transcribe`)
- **Language**: Amharic (`am`)
- **Training**: Google Colab T4 GPU, fp16, gradient checkpointing
- **Framework**: HuggingFace `transformers` + `Seq2SeqTrainer`
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## Project Structure
```
amharic-asr/
├── notebooks/
│ └── train_whisper_amharic.ipynb # Colab training notebook (runnable)
├── src/
│ ├── data_prep.py # Dat …