parallel-sentences-global-voices

# 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

# 并行语句数据集卡片：Global Voices
本数据集包含适用于多语种的并行语句（即英语语句与对应外语翻译语句的配对），其中绝大多数语料源自[OPUS网站](https://opus.nlpl.eu/)。
具体而言，本数据集涵盖了[Global Voices](https://opus.nlpl.eu/GlobalVoices/corpus/version/GlobalVoices)数据集。

## 相关数据集
以下数据集同样属于并行语句集合的组成部分：
* [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)

此类数据集可用于训练多语种语句嵌入模型。如需了解更多信息，请参阅[sbert.net - 多语种模型](https://www.sbert.net/examples/training/multilingual/README.html)。

## 数据集子集
### `all` 子集
* 字段：`english`、`non_english`
* 字段类型：`str`、`str`
* 示例：
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."
}

* 采集策略：合并本数据集的所有其他子集
* 已去重：否

### `en-…` 子集
* 字段：`english`、`non_english`
* 字段类型：`str`、`str`
* 示例：
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."
}

* 采集策略：对[parallel-sentences](https://huggingface.co/datasets/sentence-transformers/parallel-sentences)的原始数据进行处理，以Parquet格式进行格式化，随后执行去重操作
* 已去重：是