Standard
A systematic comparison of methods for low-resource dependency parsing on genuinely low-resource languages. / Vania, Clara; Kementchedjhieva, Yova; Søgaard, Anders; Lopez, Adam.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, 2019. p. 1105-1116.
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
Vania, C
, Kementchedjhieva, Y, Søgaard, A & Lopez, A 2019,
A systematic comparison of methods for low-resource dependency parsing on genuinely low-resource languages. in
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, pp. 1105-1116, Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP),
01/11/2019.
https://doi.org/10.18653/v1/D19-1102
APA
Vania, C.
, Kementchedjhieva, Y., Søgaard, A., & Lopez, A. (2019).
A systematic comparison of methods for low-resource dependency parsing on genuinely low-resource languages. In
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) (pp. 1105-1116). Association for Computational Linguistics.
https://doi.org/10.18653/v1/D19-1102
Vancouver
Vania C
, Kementchedjhieva Y, Søgaard A, Lopez A.
A systematic comparison of methods for low-resource dependency parsing on genuinely low-resource languages. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics. 2019. p. 1105-1116
https://doi.org/10.18653/v1/D19-1102
Author
Vania, Clara ; Kementchedjhieva, Yova ; Søgaard, Anders ; Lopez, Adam. / A systematic comparison of methods for low-resource dependency parsing on genuinely low-resource languages. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, 2019. pp. 1105-1116
Bibtex
@inproceedings{e5a689f69f8e4c6a862e07c0b179b485,
title = "A systematic comparison of methods for low-resource dependency parsing on genuinely low-resource languages",
abstract = "Parsers are available for only a handful of the world{\textquoteright}s languages, since they require lots of training data. How far can we get with just a small amount of training data? We systematically compare a set of simple strategies for improving low-resource parsers: data augmentation, which has not been tested before; cross-lingual training; and transliteration. Experimenting on three typologically diverse low-resource languages—North S{\'a}mi, Galician, and Kazah—We find that (1) when only the low-resource treebank is available, data augmentation is very helpful; (2) when a related high-resource treebank is available, cross-lingual training is helpful and complements data augmentation; and (3) when the high-resource treebank uses a different writing system, transliteration into a shared orthographic spaces is also very helpful.",
author = "Clara Vania and Yova Kementchedjhieva and Anders S{\o}gaard and Adam Lopez",
year = "2019",
doi = "10.18653/v1/D19-1102",
language = "English",
pages = "1105--1116",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
publisher = "Association for Computational Linguistics",
note = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) ; Conference date: 01-11-2019 Through 01-11-2019",
}
RIS
TY - GEN
T1 - A systematic comparison of methods for low-resource dependency parsing on genuinely low-resource languages
AU - Vania, Clara
AU - Kementchedjhieva, Yova
AU - Søgaard, Anders
AU - Lopez, Adam
PY - 2019
Y1 - 2019
N2 - Parsers are available for only a handful of the world’s languages, since they require lots of training data. How far can we get with just a small amount of training data? We systematically compare a set of simple strategies for improving low-resource parsers: data augmentation, which has not been tested before; cross-lingual training; and transliteration. Experimenting on three typologically diverse low-resource languages—North Sámi, Galician, and Kazah—We find that (1) when only the low-resource treebank is available, data augmentation is very helpful; (2) when a related high-resource treebank is available, cross-lingual training is helpful and complements data augmentation; and (3) when the high-resource treebank uses a different writing system, transliteration into a shared orthographic spaces is also very helpful.
AB - Parsers are available for only a handful of the world’s languages, since they require lots of training data. How far can we get with just a small amount of training data? We systematically compare a set of simple strategies for improving low-resource parsers: data augmentation, which has not been tested before; cross-lingual training; and transliteration. Experimenting on three typologically diverse low-resource languages—North Sámi, Galician, and Kazah—We find that (1) when only the low-resource treebank is available, data augmentation is very helpful; (2) when a related high-resource treebank is available, cross-lingual training is helpful and complements data augmentation; and (3) when the high-resource treebank uses a different writing system, transliteration into a shared orthographic spaces is also very helpful.
U2 - 10.18653/v1/D19-1102
DO - 10.18653/v1/D19-1102
M3 - Article in proceedings
SP - 1105
EP - 1116
BT - Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
PB - Association for Computational Linguistics
T2 - Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Y2 - 1 November 2019 through 1 November 2019
ER -