Improving sentence compression by learning to predict gaze

Sigrid Klerke; Yoav Goldberg; Anders Søgaard

Improving sentence compression by learning to predict gaze

Sigrid Klerke, Yoav Goldberg, Anders Søgaard

Institut for Nordiske Studier og Sprogvidenskab

41 Citationer (Scopus)

Abstract

We show how eye-tracking corpora can be used to improve sentence compression models, presenting a novel multi-task learning algorithm based on multi-layer LSTMs. We obtain performance competitive with or better than state-of-the-art approaches.

Originalsprog	Engelsk
Titel	Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics : Human Language Technologies
Antal sider	6
Forlag	Association for Computational Linguistics
Publikationsdato	2016
Sider	1528-1533
ISBN (Elektronisk)	978-1-941643-91-4
Status	Udgivet - 2016
Begivenhed	NAACL - San Diego, San Diego, USA Varighed: 12 jun. 2016 → 17 jun. 2016

Konference

Konference	NAACL
Lokation	San Diego
Land/Område	USA
By	San Diego
Periode	12/06/2016 → 17/06/2016

Adgang til dokumentet

http://aclweb.org/anthology/N/N16/N16-1179.pdf

Citationsformater

Improving sentence compression by learning to predict gaze. / Klerke, Sigrid; Goldberg, Yoav; Søgaard, Anders.

Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics, 2016. s. 1528-1533.

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

Klerke, S, Goldberg, Y & Søgaard, A 2016, Improving sentence compression by learning to predict gaze. i Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics, s. 1528-1533, NAACL, San Diego, USA, 12/06/2016. <http://aclweb.org/anthology/N/N16/N16-1179.pdf>

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abstract = "We show how eye-tracking corpora can be used to improve sentence compression models, presenting a novel multi-task learning algorithm based on multi-layer LSTMs. We obtain performance competitive with or better than state-of-the-art approaches.",

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booktitle = "Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics",

publisher = "Association for Computational Linguistics",

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AU - Goldberg, Yoav

AU - Søgaard, Anders

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N2 - We show how eye-tracking corpora can be used to improve sentence compression models, presenting a novel multi-task learning algorithm based on multi-layer LSTMs. We obtain performance competitive with or better than state-of-the-art approaches.

AB - We show how eye-tracking corpora can be used to improve sentence compression models, presenting a novel multi-task learning algorithm based on multi-layer LSTMs. We obtain performance competitive with or better than state-of-the-art approaches.

M3 - Article in proceedings

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BT - Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics

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ER -

Improving sentence compression by learning to predict gaze

Abstract

Konference

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