@inproceedings{gutkin-sproat-2020-nemo,
title = "{NEMO}: Frequentist Inference Approach to Constrained Linguistic Typology Feature Prediction in {SIGTYP} 2020 Shared Task",
author = "Gutkin, Alexander and
Sproat, Richard",
editor = "Vylomova, Ekaterina and
Ponti, Edoardo M. and
Grossman, Eitan and
McCarthy, Arya D. and
Berzak, Yevgeni and
Dubossarsky, Haim and
Vuli{\'c}, Ivan and
Reichart, Roi and
Korhonen, Anna and
Cotterell, Ryan",
booktitle = "Proceedings of the Second Workshop on Computational Research in Linguistic Typology",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.sigtyp-1.3",
doi = "10.18653/v1/2020.sigtyp-1.3",
pages = "17--28",
abstract = "This paper describes the NEMO submission to SIGTYP 2020 shared task (Bjerva et al., 2020) which deals with prediction of linguistic typological features for multiple languages using the data derived from World Atlas of Language Structures (WALS). We employ frequentist inference to represent correlations between typological features and use this representation to train simple multi-class estimators that predict individual features. We describe two submitted ridge regression-based configurations which ranked second and third overall in the constrained task. Our best configuration achieved the microaveraged accuracy score of 0.66 on 149 test languages.",
}
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%0 Conference Proceedings
%T NEMO: Frequentist Inference Approach to Constrained Linguistic Typology Feature Prediction in SIGTYP 2020 Shared Task
%A Gutkin, Alexander
%A Sproat, Richard
%Y Vylomova, Ekaterina
%Y Ponti, Edoardo M.
%Y Grossman, Eitan
%Y McCarthy, Arya D.
%Y Berzak, Yevgeni
%Y Dubossarsky, Haim
%Y Vulić, Ivan
%Y Reichart, Roi
%Y Korhonen, Anna
%Y Cotterell, Ryan
%S Proceedings of the Second Workshop on Computational Research in Linguistic Typology
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F gutkin-sproat-2020-nemo
%X This paper describes the NEMO submission to SIGTYP 2020 shared task (Bjerva et al., 2020) which deals with prediction of linguistic typological features for multiple languages using the data derived from World Atlas of Language Structures (WALS). We employ frequentist inference to represent correlations between typological features and use this representation to train simple multi-class estimators that predict individual features. We describe two submitted ridge regression-based configurations which ranked second and third overall in the constrained task. Our best configuration achieved the microaveraged accuracy score of 0.66 on 149 test languages.
%R 10.18653/v1/2020.sigtyp-1.3
%U https://aclanthology.org/2020.sigtyp-1.3
%U https://doi.org/10.18653/v1/2020.sigtyp-1.3
%P 17-28
Markdown (Informal)
[NEMO: Frequentist Inference Approach to Constrained Linguistic Typology Feature Prediction in SIGTYP 2020 Shared Task](https://aclanthology.org/2020.sigtyp-1.3) (Gutkin & Sproat, SIGTYP 2020)
ACL