README.md

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# ATC Dataset - Fine-Tuning Whisper

This dataset was created to fine-tune OpenAI's Whisper model for improving transcription accuracy in **Air Traffic Control (ATC)** communications. The dataset contains transcriptions and corresponding audio files from two main sources: **ATCO2** and the **UWB-ATCC corpus**, specifically selected for aviation-related communications. The dataset is publicly available on Hugging Face for use in Automatic Speech Recognition (ASR) projects.

For more details on the fine-tuning process, check out the [blog post](https://jacktol.net/posts/fine-tuning_whisper_for_atc/) and the corresponding [GitHub repository](https://github.com/jack-tol/fine-tuning-whisper-on-atc-data/tree/main).

## Dataset Overview

- **Dataset Name**: ATC Dataset
- **Total Samples**: 11.9k (Training), 2.93k (Test)
- **Data Sources**:
  - **[ATCO2 Corpus (1-hour test subset)](https://huggingface.co/datasets/Jzuluaga/atco2_corpus_1h)**
  - **[UWB-ATCC Corpus](https://huggingface.co/datasets/Jzuluaga/uwb_atcc)**
- **Format**: Audio files (WAV format) with corresponding transcriptions.
- **The Transciption Ground Truth** is within the `text` column.
- **The Audio Ground Truth** is within the `audio` column. 
- **License**: MIT

This dataset is particularly useful for training speech recognition models like Whisper on short, domain-specific audio transmissions, such as those between pilots and air traffic controllers.

### Key Features
- **Domain-specific**: Tailored to ATC communications with specialized phraseology and terms.
- **Diverse accents**: Contains multiple accent variations to reflect real-world international aviation communication.
- **Cleaned Data**: Includes only high-quality samples after filtering erroneous or incomplete transcriptions.

## Usage

1. **Install Dependencies**:  
   Use Hugging Face's `datasets` library to load the dataset:
   ```
   from datasets import load_dataset
   dataset = load_dataset("jacktol/atc-dataset")
   ```

2. **Training**:  
   The dataset is ready for speech recognition tasks such as fine-tuning Whisper models. It includes training and test splits to evaluate models based on Word Error Rate (WER).

## License

This dataset is shared under the **MIT License**. You are free to use, modify, and distribute it as long as you provide proper attribution.