高质量孟加拉语释义数据集

Q3 Environmental Science AACL Bioflux Pub Date : 2022-10-11 DOI:10.48550/arXiv.2210.05109
Ajwad Akil, Najrin Sultana, Abhik Bhattacharjee, Rifat Shahriyar
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引用次数: 4

摘要

在这项工作中,我们提出了bang腹腔镜短语,这是一个高质量的合成孟加拉语释义数据集,由一个新的过滤管道管理。我们的目标是通过引入bang腹腔镜短语来缓解孟加拉语在自然语言处理领域的低资源状态,通过保留语义和多样性来确保质量,使其对增强其他孟加拉语数据集特别有用。我们展示了我们的数据集和在其上训练的模型与其他现有作品之间的详细比较分析,以建立我们的合成释义数据生成管道的可行性。我们正在将数据集和模型在https://github.com/csebuetnlp/banglaparaphrase上公开,以进一步发展孟加拉国的自然语言处理。
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BanglaParaphrase: A High-Quality Bangla Paraphrase Dataset
In this work, we present BanglaParaphrase, a high-quality synthetic Bangla Paraphrase dataset curated by a novel filtering pipeline. We aim to take a step towards alleviating the low resource status of the Bangla language in the NLP domain through the introduction of BanglaParaphrase, which ensures quality by preserving both semantics and diversity, making it particularly useful to enhance other Bangla datasets. We show a detailed comparative analysis between our dataset and models trained on it with other existing works to establish the viability of our synthetic paraphrase data generation pipeline. We are making the dataset and models publicly available at https://github.com/csebuetnlp/banglaparaphrase to further the state of Bangla NLP.
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AACL Bioflux
AACL Bioflux Environmental Science-Management, Monitoring, Policy and Law
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