Cross-Lingual Pronoun Prediction with Deep Recurrent Neural Networks

6Citations
Citations of this article
73Readers
Mendeley users who have this article in their library.

Abstract

In this paper we present our winning system in the WMT16 Shared Task on Cross- Lingual Pronoun Prediction, where the objective is to predict a missing target language pronoun based on the target and source sentences. Our system is a deep recurrent neural network, which reads both the source language and target language context with a softmax layer making the final prediction. Our system achieves the best macro recall on all four language pairs. The margin to the next best system ranges between less than 1pp and almost 12pp depending on the language pair.

Cite

CITATION STYLE

APA

Luotolahti, J., Kanerva, J., & Ginter, F. (2016). Cross-Lingual Pronoun Prediction with Deep Recurrent Neural Networks. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (Vol. 2, pp. 596–601). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w16-2353

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free