Jonathan Washington

Also published as: Jonathan N. Washington, Jonathan North Washington


2019

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A biscriptual morphological transducer for Crimean Tatar
Francis M. Tyers | Jonathan Washington | Darya Kavitskaya | Memduh Gökırmak | Nick Howell | Remziye Berberova
Proceedings of the 3rd Workshop on the Use of Computational Methods in the Study of Endangered Languages Volume 1 (Papers)

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Proceedings of the 2nd Workshop on Technologies for MT of Low Resource Languages
Alina Karakanta | Atul Kr. Ojha | Chao-Hong Liu | Jonathan Washington | Nathaniel Oco | Surafel Melaku Lakew | Valentin Malykh | Xiaobing Zhao
Proceedings of the 2nd Workshop on Technologies for MT of Low Resource Languages

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Machine Translation for Crimean Tatar to Turkish
Memduh Gökırmak | Francis Tyers | Jonathan Washington
Proceedings of the 2nd Workshop on Technologies for MT of Low Resource Languages

2018

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Apertium’s Web Toolchain for Low-Resource Language Technology
Sushain Cherivirala | Shardul Chiplunkar | Jonathan Washington | Kevin Unhammer
Proceedings of the AMTA 2018 Workshop on Technologies for MT of Low Resource Languages (LoResMT 2018)

2017

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UD Annotatrix: An annotation tool for Universal Dependencies
Francis M. Tyers | Mariya Sheyanova | Jonathan North Washington
Proceedings of the 16th International Workshop on Treebanks and Linguistic Theories

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Syllable-aware Neural Language Models: A Failure to Beat Character-aware Ones
Zhenisbek Assylbekov | Rustem Takhanov | Bagdat Myrzakhmetov | Jonathan N. Washington
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

Syllabification does not seem to improve word-level RNN language modeling quality when compared to character-based segmentation. However, our best syllable-aware language model, achieving performance comparable to the competitive character-aware model, has 18%-33% fewer parameters and is trained 1.2-2.2 times faster.

2016

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A Finite-state Morphological Analyser for Tuvan
Francis Tyers | Aziyana Bayyr-ool | Aelita Salchak | Jonathan Washington
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

~This paper describes the development of free/open-source finite-state morphological transducers for Tuvan, a Turkic language spoken in and around the Tuvan Republic in Russia. The finite-state toolkit used for the work is the Helsinki Finite-State Toolkit (HFST), we use the lexc formalism for modelling the morphotactics and twol formalism for modelling morphophonological alternations. We present a novel description of the morphological combinatorics of pseudo-derivational morphemes in Tuvan. An evaluation is presented which shows that the transducer has a reasonable coverage―around 93%―on freely-available corpora of the languages, and high precision―over 99%―on a manually verified test set.

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Phylogenetic simulations over constraint-based grammar formalisms
Andrew Lamont | Jonathan Washington
Proceedings of the NAACL Student Research Workshop

2014

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Finite-state morphological transducers for three Kypchak languages
Jonathan Washington | Ilnar Salimzyanov | Francis Tyers
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

This paper describes the development of free/open-source finite-state morphological transducers for three Turkic languages―Kazakh, Tatar, and Kumyk―representing one language from each of the three sub-branches of the Kypchak branch of Turkic. The finite-state toolkit used for the work is the Helsinki Finite-State Toolkit (HFST). This paper describes how the development of a transducer for each subsequent closely-related language took less development time. An evaluation is presented which shows that the transducers all have a reasonable coverage―around 90\%―on freely available corpora of the languages, and high precision over a manually verified test set.

2012

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A finite-state morphological transducer for Kyrgyz
Jonathan Washington | Mirlan Ipasov | Francis Tyers
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This paper describes the development of a free/open-source finite-state morphological transducer for Kyrgyz. The transducer has been developed for morphological generation for use within a prototype Turkish→Kyrgyz machine translation system, but has also been extensively tested for analysis. The finite-state toolkit used for the work was the Helsinki Finite-State Toolkit (HFST). The paper describes some issues in Kyrgyz morphology, the development of the tool, some linguistic issues encountered and how they were dealt with, and which issues are left to resolve. An evaluation is presented which shows that the transducer has medium-level coverage, between 82% and 87% on two freely available corpora of Kyrgyz, and high precision and recall over a manually verified test set.