Datasets:

jacktol
/

ATC-ASR-Dataset

   - 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
+- Augmented training set (50% of utterances expanded with synthetic noise, pitch shift, or bandpass filtering)
+## 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)**
+  ~20 hours of ATC speech recorded over Czech airspace, featuring heavily accented English, transcription inconsistencies, and realistic code-switching artifacts.
+- **[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., `350` → `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
+- Augmenting 50% of training data with offline audio transformations
+## 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.