---
language:
- en
- multilingual
- ar
- bg
- ca
- cs
- da
- de
- el
- es
- fa
- fr
- he
- hi
- hu
- id
- it
- ko
- mk
- my
- nl
- pl
- pt
- ro
- ru
- sq
- sr
- sv
- tr
- ur
size_categories:
- 1M<n<10M
task_categories:
- feature-extraction
- sentence-similarity
pretty_name: Global Voices
tags:
- sentence-transformers
dataset_info:
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  - name: non_english
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- config_name: en-pl
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- config_name: en-sr
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- config_name: en-sv
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  - name: non_english
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  - name: train
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configs:
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  data_files:
  - split: train
    path: all/train-*
- config_name: en-ar
  data_files:
  - split: train
    path: en-ar/train-*
- config_name: en-bg
  data_files:
  - split: train
    path: en-bg/train-*
- config_name: en-ca
  data_files:
  - split: train
    path: en-ca/train-*
- config_name: en-cs
  data_files:
  - split: train
    path: en-cs/train-*
- config_name: en-da
  data_files:
  - split: train
    path: en-da/train-*
- config_name: en-de
  data_files:
  - split: train
    path: en-de/train-*
- config_name: en-el
  data_files:
  - split: train
    path: en-el/train-*
- config_name: en-es
  data_files:
  - split: train
    path: en-es/train-*
- config_name: en-fa
  data_files:
  - split: train
    path: en-fa/train-*
- config_name: en-fr
  data_files:
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    path: en-fr/train-*
- config_name: en-he
  data_files:
  - split: train
    path: en-he/train-*
- config_name: en-hi
  data_files:
  - split: train
    path: en-hi/train-*
- config_name: en-hu
  data_files:
  - split: train
    path: en-hu/train-*
- config_name: en-id
  data_files:
  - split: train
    path: en-id/train-*
- config_name: en-it
  data_files:
  - split: train
    path: en-it/train-*
- config_name: en-ko
  data_files:
  - split: train
    path: en-ko/train-*
- config_name: en-mk
  data_files:
  - split: train
    path: en-mk/train-*
- config_name: en-my
  data_files:
  - split: train
    path: en-my/train-*
- config_name: en-nl
  data_files:
  - split: train
    path: en-nl/train-*
- config_name: en-pl
  data_files:
  - split: train
    path: en-pl/train-*
- config_name: en-pt
  data_files:
  - split: train
    path: en-pt/train-*
- config_name: en-ro
  data_files:
  - split: train
    path: en-ro/train-*
- config_name: en-ru
  data_files:
  - split: train
    path: en-ru/train-*
- config_name: en-sq
  data_files:
  - split: train
    path: en-sq/train-*
- config_name: en-sr
  data_files:
  - split: train
    path: en-sr/train-*
- config_name: en-sv
  data_files:
  - split: train
    path: en-sv/train-*
- config_name: en-tr
  data_files:
  - split: train
    path: en-tr/train-*
- config_name: en-ur
  data_files:
  - split: train
    path: en-ur/train-*
---

# Dataset Card for Parallel Sentences - Global Voices

This dataset contains parallel sentences (i.e. English sentence + the same sentences in another language) for numerous other languages. Most of the sentences originate from the [OPUS website](https://opus.nlpl.eu/).
In particular, this dataset contains the [Global Voices](https://opus.nlpl.eu/GlobalVoices/corpus/version/GlobalVoices) dataset.

## Related Datasets

The following datasets are also a part of the Parallel Sentences collection:
* [parallel-sentences-europarl](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-europarl)
* [parallel-sentences-global-voices](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-global-voices)
* [parallel-sentences-muse](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-muse)
* [parallel-sentences-jw300](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-jw300)
* [parallel-sentences-news-commentary](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-news-commentary)
* [parallel-sentences-opensubtitles](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-opensubtitles)
* [parallel-sentences-talks](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-talks)
* [parallel-sentences-tatoeba](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-tatoeba)
* [parallel-sentences-wikimatrix](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-wikimatrix)
* [parallel-sentences-wikititles](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-wikititles)
* [parallel-sentences-ccmatrix](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-ccmatrix)

These datasets can be used to train multilingual sentence embedding models. For more information, see [sbert.net - Multilingual Models](https://www.sbert.net/examples/training/multilingual/README.html).

## Dataset Subsets

### `all` subset

* Columns: "english", "non_english"
* Column types: `str`, `str`
* Examples:
    ```python
    {
      "english": "We're thrilled to be honored as the jury's choice for the Best Journalistic Blog in English.",
      "non_english": "تغمرنا السعادة بهذا التكريم باختيارنا أفضل مدونة صحفية بالإنجليزية."
    }
    ```
* Collection strategy: Combining all other subsets from this dataset.
* Deduplified: No

### `en-...` subsets

* Columns: "english", "non_english"
* Column types: `str`, `str`
* Examples:
    ```python
    {
      "english": "Lisa Stone of Surfette was on the jury that chose our blog for the DW honor.",
      "non_english": "Lisa Stone, do Surfette, participou do júri que escolher o nosso blog para a honra."
    }
    ```
* Collection strategy: Processing the raw data from [parallel-sentences](https://huggingface.co/datasets/sentence-transformers/parallel-sentences) and formatting it in Parquet, followed by deduplication.
* Deduplified: Yes