activity
20182022
most citedThe SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection

14 citations · 23 across the 8 of their papers we have counts for

collaborators

11 papers

cs.CL20222 cited

Yet Another Format of Universal Dependencies for Korean

Yige Chen, Eunkyul Leah Jo, Yundong Yao +4

In this study, we propose a morpheme-based scheme for Korean dependency parsing and adopt the proposed scheme to Universal Dependencies. We present the linguistic rationale that il…

cs.CL2022

Dim Wihl Gat Tun: The Case for Linguistic Expertise in NLP for Underdocumented Languages

Clarissa Forbes, Farhan Samir, Bruce Harold Oliver +4

Recent progress in NLP is driven by pretrained models leveraging massive datasets and has predominantly benefited the world's political and economic superpowers. Technologically un…

cs.CL20221 cited

Morphological Processing of Low-Resource Languages: Where We Are and What's Next

Adam Wiemerslage, Miikka Silfverberg, Changbing Yang +4

Automatic morphological processing can aid downstream natural language processing applications, especially for low-resource languages, and assist language documentation efforts for…

cs.CL20214 cited

Translating the Unseen? Yoruba-English MT in Low-Resource, Morphologically-Unmarked Settings

Ife Adebara, Muhammad Abdul-Mageed, Miikka Silfverberg

Translating between languages where certain features are marked morphologically in one but absent or marked contextually in the other is an important test case for machine translat…

cs.CL20212 cited

Do RNN States Encode Abstract Phonological Processes?

Miikka Silfverberg, Francis Tyers, Garrett Nicolai +1

Sequence-to-sequence models have delivered impressive results in word formation tasks such as morphological inflection, often learning to model subtle morphophonological details wi…

cs.CL2020

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…