Low-resource languages: A review of past work and future challenges
A Magueresse, V Carles, E Heetderks - arXiv preprint arXiv:2006.07264, 2020 - arxiv.org
A current problem in NLP is massaging and processing low-resource languages which lack
useful training attributes such as supervised data, number of native speakers or experts, etc …
useful training attributes such as supervised data, number of native speakers or experts, etc …
Morphological Processing of Low-Resource Languages: Where We Are and What's Next
Automatic morphological processing can aid downstream natural language processing
applications, especially for low-resource languages, and assist language documentation …
applications, especially for low-resource languages, and assist language documentation …
The SIGMORPHON 2020 shared task on unsupervised morphological paradigm completion
In this paper, we describe the findings of the SIGMORPHON 2020 shared task on
unsupervised morphological paradigm completion (SIGMORPHON 2020 Task 2), a novel …
unsupervised morphological paradigm completion (SIGMORPHON 2020 Task 2), a novel …
The paradigm discovery problem
This work treats the paradigm discovery problem (PDP), the task of learning an inflectional
morphological system from unannotated sentences. We formalize the PDP and develop …
morphological system from unannotated sentences. We formalize the PDP and develop …
[PDF][PDF] Computational models of morphological learning
J Kodner - Oxford Research Encyclopedia of Linguistics, 2022 - lingbuzz.net
The most elucidating computational model of morphology learning from the perspective of a
linguist is one that learns morphology like a child does, that is, on child-like input and along …
linguist is one that learns morphology like a child does, that is, on child-like input and along …
Findings of the sigmorphon 2021 shared task on unsupervised morphological paradigm clustering
We describe the second SIGMORPHON shared task on unsupervised morphology: the goal
of the SIGMORPHON 2021 Shared Task on Unsupervised Morphological Paradigm …
of the SIGMORPHON 2021 Shared Task on Unsupervised Morphological Paradigm …
Evaluating Cross Lingual Transfer for Morphological Analysis: a Case Study of Indian Languages
S Pawar, P Bhattacharyya… - Proceedings of the 20th …, 2023 - aclanthology.org
Recent advances in pretrained multilingual models such as Multilingual T5 (mT5) have
facilitated cross-lingual transfer by learning shared representations across languages …
facilitated cross-lingual transfer by learning shared representations across languages …
Neural Arabic singular-to-plural conversion using a pretrained Character-BERT and a fused transformer
Morphological re-inflection generation is one of the most challenging tasks in the natural
language processing (NLP) domain, especially with morphologically rich, low-resource …
language processing (NLP) domain, especially with morphologically rich, low-resource …
The Zeno's Paradox ofLow-Resource'Languages
The disparity in the languages commonly studied in Natural Language Processing (NLP) is
typically reflected by referring to languages as low vs high-resourced. However, there is …
typically reflected by referring to languages as low vs high-resourced. However, there is …
Machine translation between high-resource languages in a language documentation setting
Language documentation encompasses translation, typically into the dominant high-
resource language in the region where the target language is spoken. To make data …
resource language in the region where the target language is spoken. To make data …