add readme, short version

README.md

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+---
+annotations_creators: []
+language:
+- en
+- de
+- fr
+- es
+- pl
+- it
+- ro
+- hu
+- cs
+- nl
+- fi
+- hr
+- sk
+- sl
+- et
+- lt
+language_creators: []
+license:
+- cc0
+- other
+multilinguality:
+- multilingual
+pretty_name: VoxPopuli
+size_categories: []
+source_datasets: []
+tags: []
+task_categories:
+- automatic-speech-recognition
+task_ids: []---
+
+# Dataset Card for [Dataset Name]
+
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:**
+- **Repository:** https://github.com/facebookresearch/voxpopuli
+- **Paper:** https://aclanthology.org/2021.acl-long.80/
+- **Leaderboard:**
+- **Point of Contact:** [changhan@fb.com](mailto:changhan@fb.com), [mriviere@fb.com](mailto:mriviere@fb.com), [annl@fb.com](mailto:annl@fb.com)
+
+### Dataset Summary
+
+VoxPopuli is a large-scale multilingual speech corpus for representation learning, semi-supervised learning and interpretation.
+This implementation contains transcribed speech data for 18 languages.
+It also contains 29 hours of transcribed speech data of non-native English intended for research in ASR for accented speech (15 L2 accents)
+
+The raw data is collected from 2009-2020 European Parliament event recordings. We acknowledge the European Parliament for creating and sharing these materials.
+
+### Supported Tasks and Leaderboards
+
+* automatic-speech-recognition: The dataset can be used to train a model for Automatic Speech Recognition (ASR). The model is presented with an audio file and asked to transcribe the audio file to written text. The most common evaluation metric is the word error rate (WER).
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]
+
+### Contributions
+
+Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.