@inproceedings{f29baf432a264d1481bbcdc4a9d82401,
title = "Korean morphological analysis with tied sequence-to-sequence multi-task model",
abstract = "Korean morphological analysis has been considered as a sequence of morpheme processing and POS tagging. Thus, a pipeline model of the tasks has been adopted widely by previous studies. However, the model has a problem that it cannot utilize interactions among the tasks. This paper formulates Korean morphological analysis as a combination of the tasks and presents a tied sequence-to-sequence multi-task model for training the two tasks simultaneously without any explicit regularization. The experiments prove the proposed model achieves the state-of-the-art performance.",
author = "Song, \{Hyun Je\} and Park, \{Seong Bae\}",
note = "Publisher Copyright: {\textcopyright} 2019 Association for Computational Linguistics; 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019 ; Conference date: 03-11-2019 Through 07-11-2019",
year = "2019",
doi = "10.18653/v1/d19-1150",
language = "English",
series = "EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference",
publisher = "Association for Computational Linguistics",
pages = "1436--1441",
booktitle = "EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference",
}