|
|
| ---
|
|
|
| dataset_info:
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| features:
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| - name: score
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| dtype: float32
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| - name: Kongo
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| dtype: string
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| - name: Tsonga
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| dtype: string
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| splits:
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| - name: train
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| num_bytes: 15812311
|
| num_examples: 114900
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| download_size: 15812311
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| dataset_size: 15812311
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| configs:
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| - config_name: default
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| data_files:
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| - split: train
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| path: Kongo-Tsonga_Sentence-Pairs.csv
|
|
|
| ---
|
| # Kongo-Tsonga_Sentence-Pairs Dataset
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|
|
| This dataset contains sentence pairs for African languages along with similarity scores. It can be used for machine translation, sentence alignment, or other natural language processing tasks.
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|
|
| This dataset is based on the NLLBv1 dataset, published on OPUS under an open-source initiative led by META. You can find more information here: [OPUS - NLLB-v1](https://opus.nlpl.eu/legacy/NLLB-v1.php)
|
|
|
| ## Metadata
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| - **File Name**: Kongo-Tsonga_Sentence-Pairs
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| - **Number of Rows**: 114900
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| - **Number of Columns**: 3
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| - **Columns**: score, Kongo, Tsonga
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|
|
| ## Dataset Description
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|
|
| The dataset contains sentence pairs in African languages with an associated similarity score. Each row consists of three columns:
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| 1. `score`: The similarity score between the two sentences (range from 0 to 1).
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| 2. `Kongo`: The first sentence in the pair (language 1).
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| 3. `Tsonga`: The second sentence in the pair (language 2).
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|
|
| This dataset is intended for use in training and evaluating machine learning models for tasks like translation, sentence similarity, and cross-lingual transfer learning.
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|
|
| ## References
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|
|
| Below are papers related to how the data was collected and used in various multilingual and cross-lingual applications:
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|
|
| [1] Holger Schwenk and Matthijs Douze, Learning Joint Multilingual Sentence Representations with Neural Machine Translation, ACL workshop on Representation Learning for NLP, 2017
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|
|
| [2] Holger Schwenk and Xian Li, A Corpus for Multilingual Document Classification in Eight Languages, LREC, pages 3548-3551, 2018.
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|
|
| [3] Holger Schwenk, Filtering and Mining Parallel Data in a Joint Multilingual Space ACL, July 2018
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|
|
| [4] Alexis Conneau, Guillaume Lample, Ruty Rinott, Adina Williams, Samuel R. Bowman, Holger Schwenk and Veselin Stoyanov, XNLI: Cross-lingual Sentence Understanding through Inference, EMNLP, 2018.
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|
|
| [5] Mikel Artetxe and Holger Schwenk, Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings arXiv, Nov 3 2018.
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|
|
| [6] Mikel Artetxe and Holger Schwenk, Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond arXiv, Dec 26 2018.
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|
|
| [7] Holger Schwenk, Vishrav Chaudhary, Shuo Sun, Hongyu Gong and Paco Guzman, WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia arXiv, July 11 2019.
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|
|
| [8] Holger Schwenk, Guillaume Wenzek, Sergey Edunov, Edouard Grave and Armand Joulin CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB
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|
|
| [9] Paul-Ambroise Duquenne, Hongyu Gong, Holger Schwenk, Multimodal and Multilingual Embeddings for Large-Scale Speech Mining, NeurIPS 2021, pages 15748-15761.
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|
|
| [10] Kevin Heffernan, Onur Celebi, and Holger Schwenk, Bitext Mining Using Distilled Sentence Representations for Low-Resource Languages
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|
