55 citations · 124 across the 15 of their papers we have counts for
15 papers
Multiple Sources are Better Than One: Incorporating External Knowledge in Low-Resource Glossing
Changbing Yang, Garrett Nicolai, Miikka Silfverberg
In this paper, we address the data scarcity problem in automatic data-driven glossing for low-resource languages by coordinating multiple sources of linguistic expertise. We supple…
Embedded Translations for Low-resource Automated Glossing
Changbing Yang, Garrett Nicolai, Miikka Silfverberg
We investigate automatic interlinear glossing in low-resource settings. We augment a hard-attentional neural model with embedded translation information extracted from interlinear…
An Investigation of Noise in Morphological Inflection
Adam Wiemerslage, Changbing Yang, Garrett Nicolai +2
With a growing focus on morphological inflection systems for languages where high-quality data is scarce, training data noise is a serious but so far largely ignored concern. We ai…
Understanding Compositional Data Augmentation in Typologically Diverse Morphological Inflection
Farhan Samir, Miikka Silfverberg
Data augmentation techniques are widely used in low-resource automatic morphological inflection to overcome data sparsity. However, the full implications of these techniques remain…
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…
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…
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…
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…
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…
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…
One Model to Pronounce Them All: Multilingual Grapheme-to-Phoneme Conversion With a Transformer Ensemble
Kaili Vesik, Muhammad Abdul-Mageed, Miikka Silfverberg
The task of grapheme-to-phoneme (G2P) conversion is important for both speech recognition and synthesis. Similar to other speech and language processing tasks, in a scenario where…
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…
A Finnish News Corpus for Named Entity Recognition
Teemu Ruokolainen, Pekka Kauppinen, Miikka Silfverberg +1
We present a corpus of Finnish news articles with a manually prepared named entity annotation. The corpus consists of 953 articles (193,742 word tokens) with six named entity class…
Marrying Universal Dependencies and Universal Morphology
Arya D. McCarthy, Miikka Silfverberg, Ryan Cotterell +2
The Universal Dependencies (UD) and Universal Morphology (UniMorph) projects each present schemata for annotating the morphosyntactic details of language. Each project also provide…
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…