arXiv 2205.046512022-05-10cs.CL

ParaCotta: Synthetic Multilingual Paraphrase Corpora from the Most Diverse Translation Sample Pair

Kata.ai Research Team（Kata.ai研究团队）；Kumamoto University（熊本大学）；University of Edinburgh（爱丁堡大学）；Universitas Indonesia（印度尼西亚大学）；Oracle Digital Assistant（甲骨文数字助手）；Brawijaya University（布拉维贾亚大学）

Alham Fikri Aji, Tirana Noor Fatyanosa, Radityo Eko Prasojo, Philip Arthur, Suci Fitriany, Salma Qonitah, Nadhifa Zulfa, Tomi Santoso, Mahendra Data

备注：: 10 pages, 3 figures, 6 tables. Accepted at PACLIC 2021. (ACL Anthology link: https://aclanthology.org/2021.paclic-1.56/)

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英文摘要：

We release our synthetic parallel paraphrase corpus across 17 languages: Arabic, Catalan, Czech, German, English, Spanish, Estonian, French, Hindi, Indonesian, Italian, Dutch, Romanian, Russian, Swedish, Vietnamese, and Chinese. Our method relies only on monolingual data and a neural machine translation system to generate paraphrases, hence simple to apply. We generate multiple translation samples using beam search and choose the most lexically diverse pair according to their sentence BLEU. We compare our generated corpus with the \texttt{ParaBank2}. According to our evaluation, our synthetic paraphrase pairs are semantically similar and lexically diverse.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。