1 citations · 3 across the 12 of their papers we have counts for
12 papers
Untangling the Influence of Typology, Data and Model Architecture on Ranking Transfer Languages for Cross-Lingual POS Tagging
Enora Rice, Ali Marashian, Hannah Haynie +2
Cross-lingual transfer learning is an invaluable tool for overcoming data scarcity, yet selecting a suitable transfer language remains a challenge. The precise roles of linguistic…
From Priest to Doctor: Domain Adaptation for Low-Resource Neural Machine Translation
Ali Marashian, Enora Rice, Luke Gessler +2
Many of the world's languages have insufficient data to train high-performing general neural machine translation (NMT) models, let alone domain-specific models, and often the only…
Can we teach language models to gloss endangered languages?
Michael Ginn, Mans Hulden, Alexis Palmer
Interlinear glossed text (IGT) is a popular format in language documentation projects, where each morpheme is labeled with a descriptive annotation. Automating the creation of inte…
TAMS: Translation-Assisted Morphological Segmentation
Enora Rice, Ali Marashian, Luke Gessler +2
Canonical morphological segmentation is the process of analyzing words into the standard (aka underlying) forms of their constituent morphemes. This is a core task in language docu…
GlossLM: A Massively Multilingual Corpus and Pretrained Model for Interlinear Glossed Text
Michael Ginn, Lindia Tjuatja, Taiqi He +4
Language documentation projects often involve the creation of annotated text in a format such as interlinear glossed text (IGT), which captures fine-grained morphosyntactic analyse…
Robust Generalization Strategies for Morpheme Glossing in an Endangered Language Documentation Context
Michael Ginn, Alexis Palmer
Generalization is of particular importance in resource-constrained settings, where the available training data may represent only a small fraction of the distribution of possible t…
Taxonomic Loss for Morphological Glossing of Low-Resource Languages
Michael Ginn, Alexis Palmer
Morpheme glossing is a critical task in automated language documentation and can benefit other downstream applications greatly. While state-of-the-art glossing systems perform very…
System Demo: Tool and Infrastructure for Offensive Language Error Analysis (OLEA) in English
Marie Grace, Xajavion "Jay" Seabrum, Dananjay Srinivas +1
The automatic detection of offensive language is a pressing societal need. Many systems perform well on explicit offensive language but struggle to detect more complex, nuanced, or…
A Kind Introduction to Lexical and Grammatical Aspect, with a Survey of Computational Approaches
Annemarie Friedrich, Nianwen Xue, Alexis Palmer
Aspectual meaning refers to how the internal temporal structure of situations is presented. This includes whether a situation is described as a state or as an event, whether the si…
AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages
Abteen Ebrahimi, Manuel Mager, Arturo Oncevay +14
Pretrained multilingual models are able to perform cross-lingual transfer in a zero-shot setting, even for languages unseen during pretraining. However, prior work evaluating perfo…
It's not a Non-Issue: Negation as a Source of Error in Machine Translation
Md Mosharaf Hossain, Antonios Anastasopoulos, Eduardo Blanco +1
As machine translation (MT) systems progress at a rapid pace, questions of their adequacy linger. In this study we focus on negation, a universal, core property of human language t…
A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization
Graham Neubig, Shruti Rijhwani, Alexis Palmer +21
Despite recent advances in natural language processing and other language technology, the application of such technology to language documentation and conservation has been limited…