106 citations · 177 across the 6 of their papers we have counts for
6 papers · 1 filter
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…
A Structured Variational Autoencoder for Contextual Morphological Inflection
Lawrence Wolf-Sonkin, Jason Naradowsky, Sabrina J. Mielke +1
Statistical morphological inflectors are typically trained on fully supervised, type-level data. One remaining open research question is the following: How can we effectively explo…
Are All Languages Equally Hard to Language-Model?
Ryan Cotterell, Sabrina J. Mielke, Jason Eisner +1
For general modeling methods applied to diverse languages, a natural question is: how well should we expect our models to work on languages with differing typological profiles? In…
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…
Spell Once, Summon Anywhere: A Two-Level Open-Vocabulary Language Model
Sabrina J. Mielke, Jason Eisner
We show how the spellings of known words can help us deal with unknown words in open-vocabulary NLP tasks. The method we propose can be used to extend any closed-vocabulary generat…