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--- |
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annotations_creators: |
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- expert-generated |
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language_creators: |
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- crowdsourced |
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- expert-generated |
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language: |
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- ar |
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- ca |
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- cy |
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- de |
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- es |
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- et |
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- fa |
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- fr |
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- id |
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- it |
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- ja |
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- lv |
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- mn |
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- nl |
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- pt |
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- ru |
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- sl |
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- sv |
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- ta |
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- tr |
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- zh |
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language_bcp47: |
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- sv-SE |
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- zh-CN |
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license: |
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- cc-by-nc-4.0 |
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multilinguality: |
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- multilingual |
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size_categories: |
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- 100K<n<1M |
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source_datasets: |
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- extended|other-common-voice |
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task_categories: |
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- automatic-speech-recognition |
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- audio-to-audio |
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task_ids: [] |
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paperswithcode_id: null |
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pretty_name: CoVoST 2 |
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--- |
|
|
|
# Dataset Card for covost2 |
|
|
|
## Table of Contents |
|
- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
|
- [Languages](#languages) |
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- [How to use](#how-to-use) |
|
- [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:** https://github.com/facebookresearch/covost |
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- **Repository:** https://github.com/facebookresearch/covost |
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- **Paper:** https://arxiv.org/abs/2007.10310 |
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- **Leaderboard:** [Needs More Information] |
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- **Point of Contact:** Changhan Wang (changhan@fb.com), Juan Miguel Pino (juancarabina@fb.com), Jiatao Gu (jgu@fb.com) |
|
|
|
### Dataset Summary |
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|
|
CoVoST 2 is a large-scale multilingual speech translation corpus covering translations from 21 languages into English \ |
|
and from English into 15 languages. The dataset is created using Mozillas open-source Common Voice database of \ |
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crowdsourced voice recordings. There are 2,900 hours of speech represented in the corpus. |
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|
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### Supported Tasks and Leaderboards |
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|
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`speech-translation`: The dataset can be used for Speech-to-text translation (ST). The model is presented with an audio file in one language and asked to transcribe the audio file to written text in another language. The most common evaluation metric is the BLEU score. Examples can be found at https://github.com/pytorch/fairseq/blob/master/examples/speech_to_text/docs/covost_example.md . |
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|
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### Languages |
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|
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The dataset contains the audio, transcriptions, and translations in the following languages, French, German, Dutch, Russian, Spanish, Italian, Turkish, Persian, Swedish, Mongolian, Chinese, Welsh, Catalan, Slovenian, Estonian, Indonesian, Arabic, Tamil, Portuguese, Latvian, and Japanese. |
|
|
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## How to use |
|
The `datasets` library allows you to load and pre-process your dataset in pure Python, at scale. The dataset can be downloaded and prepared in one call to your local drive by using the `load_dataset` function. |
|
|
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For example, to download the English-Turkish config, simply specify the corresponding language config name (i.e., "en_tr" for English to Turkish): |
|
```python |
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from datasets import load_dataset |
|
|
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covost2 = load_dataset("covost2", "en_tr", data_dir="<path/to/manual/data>, split="train") |
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``` |
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Note: For a successful load, you'd first need to download the Common Voice 4.0 `en` split from https://commonvoice.mozilla.org/en/datasets and unpack it with <code>tar xvzf file_name.tar</code>. Upon successful download pass the location of the CV 4.0 dataset in the `data_dir` argument of the CoVoST2 `load_dataset` call. |
|
|
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*Bonus*: create a [PyTorch dataloader](https://huggingface.co/docs/datasets/use_with_pytorch) directly with your own datasets. |
|
|
|
```python |
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from datasets import load_dataset |
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from torch.utils.data.sampler import BatchSampler, RandomSampler |
|
|
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covost2 = load_dataset("covost2", "en_tr", data_dir="<path/to/manual/data>, split="train") |
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batch_sampler = BatchSampler(RandomSampler(covost2), batch_size=32, drop_last=False) |
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dataloader = DataLoader(covost2, batch_sampler=batch_sampler) |
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``` |
|
|
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To find out more about loading and preparing audio datasets, head over to [hf.co/blog/audio-datasets](https://huggingface.co/blog/audio-datasets). |
|
|
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### Example scripts |
|
|
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Train your own CTC or Seq2Seq Speech Translation models on CoVoST2 with `transformers` - [here](https://github.com/huggingface/transformers/tree/main/examples/pytorch/speech-recognition). |
|
|
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## Dataset Structure |
|
|
|
### Data Instances |
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|
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A typical data point comprises the path to the audio file, usually called `file`, its transcription, called `sentence`, and the translation in target language called `translation`. |
|
|
|
``` |
|
{'client_id': 'd277a1f3904ae00b09b73122b87674e7c2c78e08120721f37b5577013ead08d1ea0c053ca5b5c2fb948df2c81f27179aef2c741057a17249205d251a8fe0e658', |
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'file': '/home/suraj/projects/fairseq_s2t/covst/dataset/en/clips/common_voice_en_18540003.mp3', |
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'audio': {'path': '/home/suraj/projects/fairseq_s2t/covst/dataset/en/clips/common_voice_en_18540003.mp3', |
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'array': array([-0.00048828, -0.00018311, -0.00137329, ..., 0.00079346, 0.00091553, 0.00085449], dtype=float32), |
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'sampling_rate': 48000}, |
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'id': 'common_voice_en_18540003', |
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'sentence': 'When water is scarce, avoid wasting it.', |
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'translation': 'Wenn Wasser knapp ist, verschwenden Sie es nicht.'} |
|
``` |
|
|
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### Data Fields |
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|
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- file: A path to the downloaded audio file in .mp3 format. |
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|
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- audio: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column, *i.e.* `dataset[0]["audio"]` should **always** be preferred over `dataset["audio"][0]`. |
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|
|
- sentence: The transcription of the audio file in source language. |
|
|
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- translation: The transcription of the audio file in the target language. |
|
|
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- id: unique id of the data sample. |
|
|
|
### Data Splits |
|
|
|
| config | train | validation | test | |
|
|----------|--------|------------|-------| |
|
| en_de | 289430 | 15531 | 15531 | |
|
| en_tr | 289430 | 15531 | 15531 | |
|
| en_fa | 289430 | 15531 | 15531 | |
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| en_sv-SE | 289430 | 15531 | 15531 | |
|
| en_mn | 289430 | 15531 | 15531 | |
|
| en_zh-CN | 289430 | 15531 | 15531 | |
|
| en_cy | 289430 | 15531 | 15531 | |
|
| en_ca | 289430 | 15531 | 15531 | |
|
| en_sl | 289430 | 15531 | 15531 | |
|
| en_et | 289430 | 15531 | 15531 | |
|
| en_id | 289430 | 15531 | 15531 | |
|
| en_ar | 289430 | 15531 | 15531 | |
|
| en_ta | 289430 | 15531 | 15531 | |
|
| en_lv | 289430 | 15531 | 15531 | |
|
| en_ja | 289430 | 15531 | 15531 | |
|
| fr_en | 207374 | 14760 | 14760 | |
|
| de_en | 127834 | 13511 | 13511 | |
|
| es_en | 79015 | 13221 | 13221 | |
|
| ca_en | 95854 | 12730 | 12730 | |
|
| it_en | 31698 | 8940 | 8951 | |
|
| ru_en | 12112 | 6110 | 6300 | |
|
| zh-CN_en | 7085 | 4843 | 4898 | |
|
| pt_en | 9158 | 3318 | 4023 | |
|
| fa_en | 53949 | 3445 | 3445 | |
|
| et_en | 1782 | 1576 | 1571 | |
|
| mn_en | 2067 | 1761 | 1759 | |
|
| nl_en | 7108 | 1699 | 1699 | |
|
| tr_en | 3966 | 1624 | 1629 | |
|
| ar_en | 2283 | 1758 | 1695 | |
|
| sv-SE_en | 2160 | 1349 | 1595 | |
|
| lv_en | 2337 | 1125 | 1629 | |
|
| sl_en | 1843 | 509 | 360 | |
|
| ta_en | 1358 | 384 | 786 | |
|
| ja_en | 1119 | 635 | 684 | |
|
| id_en | 1243 | 792 | 844 | |
|
| cy_en | 1241 | 690 | 690 | |
|
|
|
|
|
## Dataset Creation |
|
|
|
### Curation Rationale |
|
|
|
[Needs More Information] |
|
|
|
### Source Data |
|
|
|
#### Initial Data Collection and Normalization |
|
|
|
[Needs More Information] |
|
|
|
#### Who are the source language producers? |
|
|
|
[Needs More Information] |
|
|
|
### Annotations |
|
|
|
#### Annotation process |
|
|
|
[Needs More Information] |
|
|
|
#### Who are the annotators? |
|
|
|
[Needs More Information] |
|
|
|
### Personal and Sensitive Information |
|
|
|
The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in this dataset. |
|
|
|
## Considerations for Using the Data |
|
|
|
### Social Impact of Dataset |
|
|
|
[Needs More Information] |
|
|
|
### Discussion of Biases |
|
|
|
[Needs More Information] |
|
|
|
### Other Known Limitations |
|
|
|
[Needs More Information] |
|
|
|
## Additional Information |
|
|
|
### Dataset Curators |
|
|
|
[Needs More Information] |
|
|
|
### Licensing Information |
|
|
|
[CC BY-NC 4.0](https://github.com/facebookresearch/covost/blob/main/LICENSE) |
|
|
|
### Citation Information |
|
|
|
``` |
|
@misc{wang2020covost, |
|
title={CoVoST 2: A Massively Multilingual Speech-to-Text Translation Corpus}, |
|
author={Changhan Wang and Anne Wu and Juan Pino}, |
|
year={2020}, |
|
eprint={2007.10310}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.CL} |
|
``` |
|
|
|
### Contributions |
|
|
|
Thanks to [@patil-suraj](https://github.com/patil-suraj) for adding this dataset. |