Update README.md

README.md

@@ -22,6 +22,83 @@ dataset_info:
   download_size: 113467762
   dataset_size: 113872168.0
 ---
-# Dataset Card for "atco2_corpus_1h"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+# Dataset Card for ATCO2 test set corpus (1hr set)
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages and Other Details](#languages-and-other-details)
+- [Dataset Structure](#dataset-structure)
+  - [Data Fields](#data-fields)
+- [Additional Information](#additional-information)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+
+## Dataset Description
+- **Homepage:** [ATCO2 project homepage](https://www.atco2.org/)
+- **Repository:** [ATCO2 corpus](https://github.com/idiap/atco2-corpus)
+- **Paper:** [ATCO2 corpus: A Large-Scale Dataset for Research on Automatic Speech Recognition and Natural Language Understanding of Air Traffic Control Communications](https://arxiv.org/abs/2211.04054)
+
+### Dataset Summary
+
+ATCO2 project aims at developing a unique platform allowing to collect, organize and pre-process air-traffic control (voice communication) data from air space. This project has received funding from the Clean Sky 2 Joint Undertaking (JU) under grant agreement No 864702. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and the Clean Sky 2 JU members other than the Union.
+
+The project collected the real-time voice communication between air-traffic controllers and pilots available either directly through publicly accessible radio frequency channels or indirectly from air-navigation service providers (ANSPs). In addition to the voice communication data, contextual information is available in a form of metadata (i.e. surveillance data). The dataset consists of two distinct packages:
+
+- A corpus of 5000+ hours (pseudo-transcribed) of air-traffic control speech collected across different airports (Sion, Bern, Zurich, etc.) in .wav format for speech recognition. Speaker distribution is 90/10% between males and females and the group contains native and non-native speakers of English.
+- A corpus of 4 hours (transcribed) of air-traffic control speech collected across different airports (Sion, Bern, Zurich, etc.) in .wav format for speech recognition. Speaker distribution is 90/10% between males and females and the group contains native and non-native speakers of English. This corpus has been transcribed with orthographic information in XML format with speaker noise information, SNR values and others. Read Less
+- A free sample of the 4 hours transcribed data is in [ATCO2 project homepage](https://www.atco2.org/data)
+
+### Supported Tasks and Leaderboards
+
+- `automatic-speech-recognition`. Already adapted/fine-tuned models are available here --> [Wav2Vec 2.0 LARGE mdel](https://huggingface.co/Jzuluaga/wav2vec2-large-960h-lv60-self-en-atc-uwb-atcc-and-atcosim).
+
+### Languages and other details
+
+The text and the recordings are in English. For more information see Table 3 and Table 4 of [ATCO2 corpus paper](https://arxiv.org/abs/2211.04054)
+
+## Dataset Structure
+
+### Data Fields
+
+- `id (string)`: a string of recording identifier for each example, corresponding to its.
+- `audio (audio)`: audio data for the given ID
+- `text (string)`: transcript of the file already normalized. Follow these repositories for more details [w2v2-air-traffic](https://github.com/idiap/w2v2-air-traffic) and [bert-text-diarization-atc](https://github.com/idiap/bert-text-diarization-atc)
+- `segment_start_time (float32)`: segment start time (normally 0)
+- `segment_end_time (float32): segment end time
+- `duration (float32)`: duration of the recording, compute as segment_end_time - segment_start_time
+
+## Additional Information
+
+### Licensing Information
+
+The licensing status of the ATCO2-test-set-1h corpus is in the file **ATCO2-ASRdataset-v1_beta - End-User Data Agreement** in the data folder. Download the data in [ATCO2 project homepage](https://www.atco2.org/data)
+
+### Citation Information
+
+Contributors who prepared, processed, normalized and uploaded the dataset in HuggingFace:
+
+```
+@article{zuluaga2022how,
+    title={How Does Pre-trained Wav2Vec2. 0 Perform on Domain Shifted ASR? An Extensive Benchmark on Air Traffic Control Communications},
+    author={Zuluaga-Gomez, Juan and Prasad, Amrutha and Nigmatulina, Iuliia and Sarfjoo, Saeed and others},
+    journal={IEEE Spoken Language Technology Workshop (SLT), Doha, Qatar},
+    year={2022}
+  }
+@article{zuluaga2022bertraffic,
+  title={BERTraffic: BERT-based Joint Speaker Role and Speaker Change Detection for Air Traffic Control Communications},
+  author={Zuluaga-Gomez, Juan and Sarfjoo, Seyyed Saeed and Prasad, Amrutha and others},
+  journal={IEEE Spoken Language Technology Workshop (SLT), Doha, Qatar},
+  year={2022}
+  }
+@article{zuluaga2022atco2,
+  title={ATCO2 corpus: A Large-Scale Dataset for Research on Automatic Speech Recognition and Natural Language Understanding of Air Traffic Control Communications},
+  author={Zuluaga-Gomez, Juan and Vesel{\`y}, Karel and Sz{\"o}ke, Igor and Motlicek, Petr and others},
+  journal={arXiv preprint arXiv:2211.04054},
+  year={2022}
+}
+```
+