Search Results for author: David Yarowsky

Found 40 papers, 8 papers with code

Automatic Construction of Morphologically Motivated Translation Models for Highly Inflected, Low-Resource Languages

1 code implementation AMTA 2016 John Hewitt, Matt Post, David Yarowsky

Statistical Machine Translation (SMT) of highly inflected, low-resource languages suffers from the problem of low bitext availability, which is exacerbated by large inflectional paradigms.

Machine Translation Translation

Measuring the Similarity of Grammatical Gender Systems by Comparing Partitions

no code implementations EMNLP 2020 Arya D. McCarthy, Adina Williams, Shijia Liu, David Yarowsky, Ryan Cotterell

Of particular interest, languages on the same branch of our phylogenetic tree are notably similar, whereas languages from separate branches are no more similar than chance.

Community Detection

On Pronunciations in Wiktionary: Extraction and Experiments on Multilingual Syllabification and Stress Prediction

no code implementations RANLP (BUCC) 2021 Winston Wu, David Yarowsky

We constructed parsers for five non-English editions of Wiktionary, which combined with pronunciations from the English edition, comprises over 5. 3 million IPA pronunciations, the largest pronunciation lexicon of its kind.

Wiktionary Normalization of Translations and Morphological Information

no code implementations COLING 2020 Winston Wu, David Yarowsky

We extend the Yawipa Wiktionary Parser (Wu and Yarowsky, 2020) to extract and normalize translations from etymology glosses, and morphological form-of relations, resulting in 300K unique translations and over 4 million instances of 168 annotated morphological relations.


Fine-grained Morphosyntactic Analysis and Generation Tools for More Than One Thousand Languages

no code implementations LREC 2020 Garrett Nicolai, Dylan Lewis, Arya D. McCarthy, Aaron Mueller, Winston Wu, David Yarowsky

Exploiting the broad translation of the Bible into the world{'}s languages, we train and distribute morphosyntactic tools for approximately one thousand languages, vastly outstripping previous distributions of tools devoted to the processing of inflectional morphology.


Computational Etymology and Word Emergence

no code implementations LREC 2020 Winston Wu, David Yarowsky

We developed an extensible, comprehensive Wiktionary parser that improves over several existing parsers.

An Analysis of Massively Multilingual Neural Machine Translation for Low-Resource Languages

no code implementations LREC 2020 Aaron Mueller, Garrett Nicolai, Arya D. McCarthy, Dylan Lewis, Winston Wu, David Yarowsky

We find that best practices in this domain are highly language-specific: adding more languages to a training set is often better, but too many harms performance{---}the best number depends on the source language.

Low-Resource Neural Machine Translation Translation

Multilingual Dictionary Based Construction of Core Vocabulary

no code implementations LREC 2020 Winston Wu, Garrett Nicolai, David Yarowsky

We propose a new functional definition and construction method for core vocabulary sets for multiple applications based on the relative coverage of a target concept in thousands of bilingual dictionaries.

Cognate Prediction Machine Translation +1

Induced Inflection-Set Keyword Search in Speech

1 code implementation WS 2020 Oliver Adams, Matthew Wiesner, Jan Trmal, Garrett Nicolai, David Yarowsky

We investigate the problem of searching for a lexeme-set in speech by searching for its inflectional variants.

Modeling Color Terminology Across Thousands of Languages

1 code implementation IJCNLP 2019 Arya D. McCarthy, Winston Wu, Aaron Mueller, Bill Watson, David Yarowsky

There is an extensive history of scholarship into what constitutes a "basic" color term, as well as a broadly attested acquisition sequence of basic color terms across many languages, as articulated in the seminal work of Berlin and Kay (1969).

The CoNLL--SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection

no code implementations CONLL 2018 Ryan Cotterell, Christo Kirov, John Sylak-Glassman, Géraldine Walther, Ekaterina Vylomova, Arya D. McCarthy, Katharina Kann, Sabrina J. Mielke, Garrett Nicolai, Miikka Silfverberg, David Yarowsky, Jason Eisner, Mans Hulden

Apart from extending the number of languages involved in earlier supervised tasks of generating inflected forms, this year the shared task also featured a new second task which asked participants to inflect words in sentential context, similar to a cloze task.

Marrying Universal Dependencies and Universal Morphology

no code implementations WS 2018 Arya D. McCarthy, Miikka Silfverberg, Ryan Cotterell, Mans Hulden, David Yarowsky

The Universal Dependencies (UD) and Universal Morphology (UniMorph) projects each present schemata for annotating the morphosyntactic details of language.

Paradigm Completion for Derivational Morphology

no code implementations EMNLP 2017 Ryan Cotterell, Ekaterina Vylomova, Huda Khayrallah, Christo Kirov, David Yarowsky

The generation of complex derived word forms has been an overlooked problem in NLP; we fill this gap by applying neural sequence-to-sequence models to the task.

CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection in 52 Languages

no code implementations CONLL 2017 Ryan Cotterell, Christo Kirov, John Sylak-Glassman, Géraldine Walther, Ekaterina Vylomova, Patrick Xia, Manaal Faruqui, Sandra Kübler, David Yarowsky, Jason Eisner, Mans Hulden

In sub-task 2, systems were given a lemma and some of its specific inflected forms, and asked to complete the inflectional paradigm by predicting all of the remaining inflected forms.

Data Augmentation

Remote Elicitation of Inflectional Paradigms to Seed Morphological Analysis in Low-Resource Languages

no code implementations LREC 2016 John Sylak-Glassman, Christo Kirov, David Yarowsky

We present methods inspired by linguistic fieldwork for gathering inflectional paradigm data in a machine-readable, interoperable format from remotely-located speakers of any language.

Morphological Analysis

Very-large Scale Parsing and Normalization of Wiktionary Morphological Paradigms

no code implementations LREC 2016 Christo Kirov, John Sylak-Glassman, Roger Que, David Yarowsky

Wiktionary is a large-scale resource for cross-lingual lexical information with great potential utility for machine translation (MT) and many other NLP tasks, especially automatic morphological analysis and generation.

Machine Translation Morphological Analysis +1

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