Cross-Lingual Pronoun Prediction with Deep Recurrent Neural Networks v2.0

Juhani Luotolahti, Jenna Kanerva, Filip Ginter


Abstract
In this paper we present our system in the DiscoMT 2017 Shared Task on Crosslingual Pronoun Prediction. Our entry builds on our last year’s success, our system based on deep recurrent neural networks outperformed all the other systems with a clear margin. This year we investigate whether different pre-trained word embeddings can be used to improve the neural systems, and whether the recently published Gated Convolutions outperform the Gated Recurrent Units used last year.
Anthology ID:
W17-4808
Volume:
Proceedings of the Third Workshop on Discourse in Machine Translation
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Editors:
Bonnie Webber, Andrei Popescu-Belis, Jörg Tiedemann
Venue:
DiscoMT
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
63–66
Language:
URL:
https://aclanthology.org/W17-4808
DOI:
10.18653/v1/W17-4808
Bibkey:
Cite (ACL):
Juhani Luotolahti, Jenna Kanerva, and Filip Ginter. 2017. Cross-Lingual Pronoun Prediction with Deep Recurrent Neural Networks v2.0. In Proceedings of the Third Workshop on Discourse in Machine Translation, pages 63–66, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
Cross-Lingual Pronoun Prediction with Deep Recurrent Neural Networks v2.0 (Luotolahti et al., DiscoMT 2017)
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PDF:
https://aclanthology.org/W17-4808.pdf