@inproceedings{choudhary-2020-nuig,
title = "{NUIG}: Multitasking Self-attention based approach to {S}ig{T}yp 2020 Shared Task",
author = "Choudhary, Chinmay",
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-1.6",
doi = "10.18653/v1/2020.sigtyp-1.6",
pages = "43--50",
abstract = "The paper describes the \textit{Multitasking Self-attention based approach} to constrained sub-task within Sigtyp 2020 Shared task. Our model is simple neural network based architecture inspired by Transformers (CITATION) model. The model uses Multitasking to compute values of all WALS features for a given input language simultaneously.Results show that our approach performs at par with the baseline approaches, even though our proposed approach requires only phylogenetic and geographical attributes namely \textit{Longitude}, \textit{Latitude}, \textit{Genus-index}, \textit{Family-index} and \textit{Country-index} and do not use any of the known WALS features of the respective input language, to compute its missing WALS features.",
}
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<abstract>The paper describes the Multitasking Self-attention based approach to constrained sub-task within Sigtyp 2020 Shared task. Our model is simple neural network based architecture inspired by Transformers (CITATION) model. The model uses Multitasking to compute values of all WALS features for a given input language simultaneously.Results show that our approach performs at par with the baseline approaches, even though our proposed approach requires only phylogenetic and geographical attributes namely Longitude, Latitude, Genus-index, Family-index and Country-index and do not use any of the known WALS features of the respective input language, to compute its missing WALS features.</abstract>
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%0 Conference Proceedings
%T NUIG: Multitasking Self-attention based approach to SigTyp 2020 Shared Task
%A Choudhary, Chinmay
%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 choudhary-2020-nuig
%X The paper describes the Multitasking Self-attention based approach to constrained sub-task within Sigtyp 2020 Shared task. Our model is simple neural network based architecture inspired by Transformers (CITATION) model. The model uses Multitasking to compute values of all WALS features for a given input language simultaneously.Results show that our approach performs at par with the baseline approaches, even though our proposed approach requires only phylogenetic and geographical attributes namely Longitude, Latitude, Genus-index, Family-index and Country-index and do not use any of the known WALS features of the respective input language, to compute its missing WALS features.
%R 10.18653/v1/2020.sigtyp-1.6
%U https://aclanthology.org/2020.sigtyp-1.6
%U https://doi.org/10.18653/v1/2020.sigtyp-1.6
%P 43-50
Markdown (Informal)
[NUIG: Multitasking Self-attention based approach to SigTyp 2020 Shared Task](https://aclanthology.org/2020.sigtyp-1.6) (Choudhary, SIGTYP 2020)
ACL