Natural language processing (NLP) systems have become a central technology in
communication, education, medicine, artificial intelligence, and many other domains of …

Viable cross-lingual transfer critically depends on the availability of parallel texts. Shortage
of such resources imposes a development and evaluation bottleneck in multilingual …

Flexible neural sequence models outperform grammar-and automaton-based counterparts
on a variety of tasks. However, neural models perform poorly in settings requiring …

The Universal Morphology (UniMorph) project is a collaborative effort providing broad-
coverage instantiated normalized morphological paradigms for hundreds of diverse world …

The CoNLL--SIGMORPHON 2018 shared task on supervised learning of morphological
generation featured data sets from 103 typologically diverse languages. Apart from …

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 …

We present findings from the creation of a massively parallel corpus in over 1600
languages, the Johns Hopkins University Bible Corpus (JHUBC). The corpus consists of …

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 this …

How language-agnostic are current state-of-the-art NLP tools? Are there some types of
language that are easier to model with current methods? In prior work (Cotterell et al., 2018) …

We introduce WikiPron, an open-source command-line tool for extracting pronunciation data
from Wiktionary, a collaborative multilingual online dictionary. We first describe the design …