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        <title>Unsupervised Text Segmentation Based on Native Language Characteristics</title>
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    <name type="personal">
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            <namePart type="given">Min-Yen</namePart>
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    <abstract>Most work on segmenting text does so on the basis of topic changes, but it can be of interest to segment by other, stylistically expressed characteristics such as change of authorship or native language. We propose a Bayesian unsupervised text segmentation approach to the latter. While baseline models achieve essentially random segmentation on our task, indicating its difficulty, a Bayesian model that incorporates appropriately compact language models and alternating asymmetric priors can achieve scores on the standard metrics around halfway to perfect segmentation.</abstract>
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%0 Conference Proceedings
%T Unsupervised Text Segmentation Based on Native Language Characteristics
%A Malmasi, Shervin
%A Dras, Mark
%A Johnson, Mark
%A Du, Lan
%A Wolska, Magdalena
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F malmasi-etal-2017-unsupervised
%X Most work on segmenting text does so on the basis of topic changes, but it can be of interest to segment by other, stylistically expressed characteristics such as change of authorship or native language. We propose a Bayesian unsupervised text segmentation approach to the latter. While baseline models achieve essentially random segmentation on our task, indicating its difficulty, a Bayesian model that incorporates appropriately compact language models and alternating asymmetric priors can achieve scores on the standard metrics around halfway to perfect segmentation.
%R 10.18653/v1/P17-1134
%U https://aclanthology.org/P17-1134
%U https://doi.org/10.18653/v1/P17-1134
%P 1457-1469

Markdown (Informal)

[Unsupervised Text Segmentation Based on Native Language Characteristics](https://aclanthology.org/P17-1134) (Malmasi et al., ACL 2017)

• Unsupervised Text Segmentation Based on Native Language Characteristics (Malmasi et al., ACL 2017)

ACL

• Shervin Malmasi, Mark Dras, Mark Johnson, Lan Du, and Magdalena Wolska. 2017. Unsupervised Text Segmentation Based on Native Language Characteristics. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1457–1469, Vancouver, Canada. Association for Computational Linguistics.