98 citations · 257 across the 14 of their papers we have counts for
17 papers
Improving Informally Romanized Language Identification
Adrian Benton, Alexander Gutkin, Christo Kirov +1
The Latin script is often used to informally write languages with non-Latin native scripts. In many cases (e.g., most languages in India), the lack of conventional spelling in the…
XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages
Sebastian Ruder, Jonathan H. Clark, Alexander Gutkin +24
Data scarcity is a crucial issue for the development of highly multilingual NLP systems. Yet for many under-represented languages (ULs) -- languages for which NLP re-search is part…
Spelling convention sensitivity in neural language models
Elizabeth Nielsen, Christo Kirov, Brian Roark
We examine whether large neural language models, trained on very large collections of varied English text, learn the potentially long-distance dependency of British versus American…
UniMorph 4.0: Universal Morphology
Khuyagbaatar Batsuren, Omer Goldman, Salam Khalifa +93
The Universal Morphology (UniMorph) project is a collaborative effort providing broad-coverage instantiated normalized morphological inflection tables for hundreds of diverse world…
Structured abbreviation expansion in context
Kyle Gorman, Christo Kirov, Brian Roark +1
Ad hoc abbreviations are commonly found in informal communication channels that favor shorter messages. We consider the task of reversing these abbreviations in context to recover…
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection
Ekaterina Vylomova, Jennifer White, Elizabeth Salesky +25
A broad goal in natural language processing (NLP) is to develop a system that has the capacity to process any natural language. Most systems, however, are developed using data from…
Processing South Asian Languages Written in the Latin Script: the Dakshina Dataset
Brian Roark, Lawrence Wolf-Sonkin, Christo Kirov +4
This paper describes the Dakshina dataset, a new resource consisting of text in both the Latin and native scripts for 12 South Asian languages. The dataset includes, for each langu…
Neural Polysynthetic Language Modelling
Lane Schwartz, Francis Tyers, Lori Levin +18
Research in natural language processing commonly assumes that approaches that work well for English and and other widely-used languages are "language agnostic". In high-resource la…
The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection
Arya D. McCarthy, Ekaterina Vylomova, Shijie Wu +9
The SIGMORPHON 2019 shared task on cross-lingual transfer and contextual analysis in morphology examined transfer learning of inflection between 100 language pairs, as well as cont…
UniMorph 2.0: Universal Morphology
Christo Kirov, Ryan Cotterell, John Sylak-Glassman +10
The Universal Morphology UniMorph project is a collaborative effort to improve how NLP handles complex morphology across the world's languages. The project releases annotated morph…
The CoNLL--SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection
Ryan Cotterell, Christo Kirov, John Sylak-Glassman +10
The CoNLL--SIGMORPHON 2018 shared task on supervised learning of morphological generation featured data sets from 103 typologically diverse languages. Apart from extending the numb…
On the Complexity and Typology of Inflectional Morphological Systems
Ryan Cotterell, Christo Kirov, Mans Hulden +1
We quantify the linguistic complexity of different languages' morphological systems. We verify that there is an empirical trade-off between paradigm size and irregularity: a langua…
Recurrent Neural Networks in Linguistic Theory: Revisiting Pinker and Prince (1988) and the Past Tense Debate
Christo Kirov, Ryan Cotterell
Can advances in NLP help advance cognitive modeling? We examine the role of artificial neural networks, the current state of the art in many common NLP tasks, by returning to a cla…
Unsupervised Disambiguation of Syncretism in Inflected Lexicons
Ryan Cotterell, Christo Kirov, Sabrina J. Mielke +1
Lexical ambiguity makes it difficult to compute various useful statistics of a corpus. A given word form might represent any of several morphological feature bundles. One can, howe…
On the Diachronic Stability of Irregularity in Inflectional Morphology
Ryan Cotterell, Christo Kirov, Mans Hulden +1
Many languages' inflectional morphological systems are replete with irregulars, i.e., words that do not seem to follow standard inflectional rules. In this work, we quantitatively…
Paradigm Completion for Derivational Morphology
Ryan Cotterell, Ekaterina Vylomova, Huda Khayrallah +2
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. We overview the the…
CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection in 52 Languages
Ryan Cotterell, Christo Kirov, John Sylak-Glassman +8
The CoNLL-SIGMORPHON 2017 shared task on supervised morphological generation required systems to be trained and tested in each of 52 typologically diverse languages. In sub-task 1,…