@inproceedings{chaudhary-etal-2019-cmu,
title = "{CMU}-01 at the {SIGMORPHON} 2019 Shared Task on Crosslinguality and Context in Morphology",
author = "Chaudhary, Aditi and
Salesky, Elizabeth and
Bhat, Gayatri and
Mortensen, David R. and
Carbonell, Jaime and
Tsvetkov, Yulia",
editor = "Nicolai, Garrett and
Cotterell, Ryan",
booktitle = "Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-4208",
doi = "10.18653/v1/W19-4208",
pages = "57--70",
abstract = "This paper presents the submission by the CMU-01 team to the SIGMORPHON 2019 task 2 of Morphological Analysis and Lemmatization in Context. This task requires us to produce the lemma and morpho-syntactic description of each token in a sequence, for 107 treebanks. We approach this task with a hierarchical neural conditional random field (CRF) model which predicts each coarse-grained feature (eg. POS, Case, etc.) independently. However, most treebanks are under-resourced, thus making it challenging to train deep neural models for them. Hence, we propose a multi-lingual transfer training regime where we transfer from multiple related languages that share similar typology.",
}
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<abstract>This paper presents the submission by the CMU-01 team to the SIGMORPHON 2019 task 2 of Morphological Analysis and Lemmatization in Context. This task requires us to produce the lemma and morpho-syntactic description of each token in a sequence, for 107 treebanks. We approach this task with a hierarchical neural conditional random field (CRF) model which predicts each coarse-grained feature (eg. POS, Case, etc.) independently. However, most treebanks are under-resourced, thus making it challenging to train deep neural models for them. Hence, we propose a multi-lingual transfer training regime where we transfer from multiple related languages that share similar typology.</abstract>
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%0 Conference Proceedings
%T CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology
%A Chaudhary, Aditi
%A Salesky, Elizabeth
%A Bhat, Gayatri
%A Mortensen, David R.
%A Carbonell, Jaime
%A Tsvetkov, Yulia
%Y Nicolai, Garrett
%Y Cotterell, Ryan
%S Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F chaudhary-etal-2019-cmu
%X This paper presents the submission by the CMU-01 team to the SIGMORPHON 2019 task 2 of Morphological Analysis and Lemmatization in Context. This task requires us to produce the lemma and morpho-syntactic description of each token in a sequence, for 107 treebanks. We approach this task with a hierarchical neural conditional random field (CRF) model which predicts each coarse-grained feature (eg. POS, Case, etc.) independently. However, most treebanks are under-resourced, thus making it challenging to train deep neural models for them. Hence, we propose a multi-lingual transfer training regime where we transfer from multiple related languages that share similar typology.
%R 10.18653/v1/W19-4208
%U https://aclanthology.org/W19-4208
%U https://doi.org/10.18653/v1/W19-4208
%P 57-70
Markdown (Informal)
[CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology](https://aclanthology.org/W19-4208) (Chaudhary et al., ACL 2019)
ACL
- Aditi Chaudhary, Elizabeth Salesky, Gayatri Bhat, David R. Mortensen, Jaime Carbonell, and Yulia Tsvetkov. 2019. CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology. In Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology, pages 57–70, Florence, Italy. Association for Computational Linguistics.