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        <title>That Slepen Al the Nyght with Open Ye! Cross-era Sequence Segmentation with Switch-memory</title>
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    <abstract>The evolution of language follows the rule of gradual change. Grammar, vocabulary, and lexical semantic shifts take place over time, resulting in a diachronic linguistic gap. As such, a considerable amount of texts are written in languages of different eras, which creates obstacles for natural language processing tasks, such as word segmentation and machine translation. Although the Chinese language has a long history, previous Chinese natural language processing research has primarily focused on tasks within a specific era. Therefore, we propose a cross-era learning framework for Chinese word segmentation (CWS), CROSSWISE, which uses the Switch-memory (SM) module to incorporate era-specific linguistic knowledge. Experiments on four corpora from different eras show that the performance of each corpus significantly improves. Further analyses also demonstrate that the SM can effectively integrate the knowledge of the eras into the neural network.</abstract>
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%0 Conference Proceedings
%T That Slepen Al the Nyght with Open Ye! Cross-era Sequence Segmentation with Switch-memory
%A Tang, Xuemei
%A Su, Qi
%Y Muresan, Smaranda
%Y Nakov, Preslav
%Y Villavicencio, Aline
%S Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F tang-su-2022-slepen
%X The evolution of language follows the rule of gradual change. Grammar, vocabulary, and lexical semantic shifts take place over time, resulting in a diachronic linguistic gap. As such, a considerable amount of texts are written in languages of different eras, which creates obstacles for natural language processing tasks, such as word segmentation and machine translation. Although the Chinese language has a long history, previous Chinese natural language processing research has primarily focused on tasks within a specific era. Therefore, we propose a cross-era learning framework for Chinese word segmentation (CWS), CROSSWISE, which uses the Switch-memory (SM) module to incorporate era-specific linguistic knowledge. Experiments on four corpora from different eras show that the performance of each corpus significantly improves. Further analyses also demonstrate that the SM can effectively integrate the knowledge of the eras into the neural network.
%R 10.18653/v1/2022.acl-long.540
%U https://aclanthology.org/2022.acl-long.540
%U https://doi.org/10.18653/v1/2022.acl-long.540
%P 7830-7840

Markdown (Informal)

[That Slepen Al the Nyght with Open Ye! Cross-era Sequence Segmentation with Switch-memory](https://aclanthology.org/2022.acl-long.540) (Tang & Su, ACL 2022)

• That Slepen Al the Nyght with Open Ye! Cross-era Sequence Segmentation with Switch-memory (Tang & Su, ACL 2022)

ACL

• Xuemei Tang and Qi Su. 2022. That Slepen Al the Nyght with Open Ye! Cross-era Sequence Segmentation with Switch-memory. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 7830–7840, Dublin, Ireland. Association for Computational Linguistics.