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        <title>Quality Does Matter: A Detailed Look at the Quality and Utility of Web-Mined Parallel Corpora</title>
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        <namePart type="given">Surangika</namePart>
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        <namePart type="given">Aloka</namePart>
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    <abstract>We conducted a detailed analysis on the quality of web-mined corpora for two low-resource languages (making three language pairs, English-Sinhala, English-Tamil and Sinhala-Tamil). We ranked each corpus according to a similarity measure and carried out an intrinsic and extrinsic evaluation on different portions of this ranked corpus. We show that there are significant quality differences between different portions of web-mined corpora and that the quality varies across languages and datasets. We also show that, for some web-mined datasets, Neural Machine Translation (NMT) models trained with their highest-ranked 25k portion can be on par with human-curated datasets.</abstract>
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%0 Conference Proceedings
%T Quality Does Matter: A Detailed Look at the Quality and Utility of Web-Mined Parallel Corpora
%A Ranathunga, Surangika
%A De Silva, Nisansa
%A Menan, Velayuthan
%A Fernando, Aloka
%A Rathnayake, Charitha
%Y Graham, Yvette
%Y Purver, Matthew
%S Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julian’s, Malta
%F ranathunga-etal-2024-quality
%X We conducted a detailed analysis on the quality of web-mined corpora for two low-resource languages (making three language pairs, English-Sinhala, English-Tamil and Sinhala-Tamil). We ranked each corpus according to a similarity measure and carried out an intrinsic and extrinsic evaluation on different portions of this ranked corpus. We show that there are significant quality differences between different portions of web-mined corpora and that the quality varies across languages and datasets. We also show that, for some web-mined datasets, Neural Machine Translation (NMT) models trained with their highest-ranked 25k portion can be on par with human-curated datasets.
%U https://aclanthology.org/2024.eacl-long.52/
%P 860-880

Markdown (Informal)

[Quality Does Matter: A Detailed Look at the Quality and Utility of Web-Mined Parallel Corpora](https://aclanthology.org/2024.eacl-long.52/) (Ranathunga et al., EACL 2024)

• Quality Does Matter: A Detailed Look at the Quality and Utility of Web-Mined Parallel Corpora (Ranathunga et al., EACL 2024)

ACL

• Surangika Ranathunga, Nisansa De Silva, Velayuthan Menan, Aloka Fernando, and Charitha Rathnayake. 2024. Quality Does Matter: A Detailed Look at the Quality and Utility of Web-Mined Parallel Corpora. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pages 860–880, St. Julian’s, Malta. Association for Computational Linguistics.