| | --- |
| | dataset_info: |
| | features: |
| | - name: id |
| | dtype: string |
| | - name: audio |
| | dtype: audio |
| | - name: text |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 692440565.782 |
| | num_examples: 6497 |
| | - name: validation |
| | num_bytes: 86238362.0 |
| | num_examples: 812 |
| | - name: test |
| | num_bytes: 87842088.0 |
| | num_examples: 813 |
| | download_size: 848224655 |
| | dataset_size: 866521015.782 |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: train |
| | path: data/train-* |
| | - split: validation |
| | path: data/validation-* |
| | - split: test |
| | path: data/test-* |
| | --- |
| | |
| | # ATC ASR Dataset |
| |
|
| | **ATC ASR Dataset** is a high-quality, fine-tuning-ready speech recognition dataset constructed from two real-world Air Traffic Control (ATC) corpora: the [UWB ATC Corpus](https://lindat.mff.cuni.cz/repository/xmlui/handle/11858/00-097C-0000-0001-CCA1-0) and the [ATCO2 1-Hour Test Subset](https://www.replaywell.com/atco2/download/ATCO2-ASRdataset-v1_beta.tgz). |
| |
|
| | The dataset consists of cleanly segmented `audio + transcript` pairs at the utterance level, specifically curated for Automatic Speech Recognition (ASR) training and fine-tuning in the ATC domain. |
| |
|
| | ## Contents |
| |
|
| | This dataset includes: |
| |
|
| | - Audio files (`.wav`, 16kHz mono) of individual ATC utterances |
| | - Transcripts (`.txt`) aligned with each audio file |
| | - Training, validation, and test splits |
| |
|
| | ## Use Cases |
| |
|
| | This dataset is ideal for: |
| |
|
| | - Training ASR models specialized in aviation communication |
| | - Benchmarking domain-adapted speech recognition systems |
| | - Studying accented and noisy English in operational ATC environments |
| |
|
| | ## Source Datasets |
| |
|
| | This dataset combines data from: |
| |
|
| | - **[UWB ATC Corpus](https://lindat.mff.cuni.cz/repository/xmlui/handle/11858/00-097C-0000-0001-CCA1-0)** - ATC speech and corresponding transcripts recorded over Czech airspace, featuring heavily accented English. |
| |
|
| | - **[ATCO2 1-Hour Test Subset](https://www.replaywell.com/atco2/download/ATCO2-ASRdataset-v1_beta.tgz)** - A publicly released evaluation slice from the larger ATCO2 corpus, featuring diverse ATC environments, speaker accents, and acoustic conditions. |
| |
|
| | ## Cleaning & Preprocessing |
| |
|
| | The raw corpora were normalized and cleaned using custom Python scripts. Key steps included: |
| |
|
| | - Segmenting long audio files into utterance-level clips using timestamps |
| | - Uppercasing all transcripts for uniformity |
| | - Converting digits to words (e.g., `3 5 0` → `THREE FIVE ZERO`) |
| | - Expanding letters to phonetic alphabet equivalents (e.g., `N` → `NOVEMBER`) |
| | - Removing non-English, unintelligible, or corrupted segments |
| | - Normalizing diacritics and fixing broken Unicode characters |
| | - Manual filtering of misaligned or low-quality samples |
| |
|
| | ## Usage |
| |
|
| | 1. **Install Dependencies**: |
| | Use Hugging Face's `datasets` library to load the dataset: |
| | ``` |
| | from datasets import load_dataset |
| | dataset = load_dataset("jacktol/ATC-ASR-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). |
| |
|
| | ## Reproducibility |
| |
|
| | All preprocessing scripts and data creation pipelines are publicly available in the companion GitHub repository: |
| |
|
| | [ATC ASR Dataset Preparation Toolkit (GitHub)](https://github.com/jack-tol/atc-asr-dataset-preparation-toolkit) |
| |
|
| | This includes: |
| |
|
| | - Scripts to process raw UWB, ATCO2, and ATCC datasets |
| | - Tools for combining, splitting, and augmenting data |
| | - Upload scripts for Hugging Face dataset integration |
| |
|
| | ## References |
| |
|
| | - [ATC ASR_Dataset (Combined and Cleaned Dataset on Hugging Face)](https://huggingface.co/datasets/jacktol/ATC_ASR_Dataset) |
| | - [ATC ASR Dataset Preparation Toolkit (GitHub Repository)](https://github.com/jack-tol/atc-asr-dataset-preparation-toolkit) |
| | - [ATCC Corpus (LDC94S14A, Raw)](https://catalog.ldc.upenn.edu/LDC94S14A) |
| | - [ATCO2 1-Hour Test Subset (Raw)](https://www.replaywell.com/atco2/download/ATCO2-ASRdataset-v1_beta.tgz) |
| | - [Juan Pablo Zuluaga – UWB ATC Dataset on GitHub](https://github.com/idiap/atco2-corpus/tree/main/data/databases/uwb_atcc) |
| | - [Juan Pablo Zuluaga – UWB ATC Dataset on Hugging Face](https://huggingface.co/datasets/Jzuluaga/uwb_atcc) |
| | - [UWB ATC Corpus (Raw)](https://lindat.mff.cuni.cz/repository/xmlui/handle/11858/00-097C-0000-0001-CCA1-0) |
| |
|
| |
|
| | ## Citation |
| |
|
| | If you use this dataset, please cite the original UWB and ATCO2 corpora where appropriate. |
| | For data processing methodology and code, reference the [ATC ASR Dataset Preparation Toolkit](https://github.com/jack-tol/atc-asr-dataset-preparation-toolkit). |
| |
|
| | Mentioning or linking to this Hugging Face dataset page helps support transparency and future development of open ATC ASR resources. |
