# kinyarwanda-asr-track-a
# π·πΌ Kinyarwanda ASR β Track A
This repository contains our solution for the **Kinyarwanda Automatic Speech Recognition (ASR) Hackathon β Track A**, hosted on Kaggle.
We develop an ASR model using mel spectrograms, character-level tokenization, and a GRU-based encoder-decoder trained with CTC loss.
## π Structure
- `notebooks/` β Jupyter/Kaggle notebooks
- `models/` β GRU-based model and training logic
- `utils/` β Tokenizer, Dataset, Config files
- `train.py` β Optional script for local training
- `data/` β Placeholder (data comes from Kaggle competition)
## π Current Baseline
- Model: GRU encoder with CNN front-end
- Features: Mel spectrograms (128 dims)
- Loss: CTC
- Tokenizer: Character-based with special tokens
## π Evaluation
We use the official metrics: