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
- 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)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W17-4808.pdf