Datasets:

Multilinguality:
translation
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1M<n<10M
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found
Annotations Creators:
no-annotation
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YAML Metadata Warning: The task_categories "conditional-text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, other
YAML Metadata Warning: The task_ids "machine-translation" is not in the official list: acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-modeling, dialogue-generation, conversational, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering

Dataset Card for MTet

Dataset Summary

MTet (Multi-domain Translation for English-Vietnamese) dataset contains roughly 4.2 million English-Vietnamese pairs of texts, ranging across multiple different domains such as medical publications, religious texts, engineering articles, literature, news, and poems.

This dataset extends our previous SAT (Style Augmented Translation) dataset (v1.0) by adding more high-quality English-Vietnamese sentence pairs on various domains.

Supported Tasks and Leaderboards

  • Machine Translation

Languages

The languages in the dataset are:

  • Vietnamese (vi)
  • English (en)

Dataset Structure

Data Instances

{
  'translation': {
    'en': 'He said that existing restrictions would henceforth be legally enforceable, and violators would be fined.',
    'vi': 'Ông nói những biện pháp hạn chế hiện tại sẽ được nâng lên thành quy định pháp luật, và những ai vi phạm sẽ chịu phạt.'
  }
}

Data Fields

  • translation:
    • en: Parallel text in English.
    • vi: Parallel text in Vietnamese.

Data Splits

The dataset is in a single "train" split.

train
Number of examples 4163853

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

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).

Citation Information

@article{mTet2022,
    author  = {Chinh Ngo, Hieu Tran, Long Phan, Trieu H. Trinh, Hieu Nguyen, Minh Nguyen, Minh-Thang Luong},
    title   = {MTet: Multi-domain Translation for English and Vietnamese},
    journal = {https://github.com/vietai/mTet},
    year    = {2022},
}

Contributions

Thanks to @albertvillanova for adding this dataset.

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