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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A2SBUITQ6" target="_blank" >RIV/00216208:11320/22:2SBUITQ6 - isvavai.cz</a>

Výsledek na webu

<a href="https://aclanthology.org/2022.findings-acl.80" target="_blank" >https://aclanthology.org/2022.findings-acl.80</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.18653/v1/2022.findings-acl.80" target="_blank" >10.18653/v1/2022.findings-acl.80</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

Automatic morphological processing can aid downstream natural language processing applications, especially for low-resource languages, and assist language documentation efforts for endangered languages. Having long been multilingual, the field of computational morphology is increasingly moving towards approaches suitable for languages with minimal or no annotated resources. First, we survey recent developments in computational morphology with a focus on low-resource languages. Second, we argue that the field is ready to tackle the logical next challenge: understanding a language's morphology from raw text alone. We perform an empirical study on a truly unsupervised version of the paradigm completion task and show that, while existing state-of-the-art models bridged by two newly proposed models we devise perform reasonably, there is still much room for improvement. The stakes are high: solving this task will increase the language coverage of morphological resources by a number of magnitudes.

Název v anglickém jazyce

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

Popis výsledku anglicky

Automatic morphological processing can aid downstream natural language processing applications, especially for low-resource languages, and assist language documentation efforts for endangered languages. Having long been multilingual, the field of computational morphology is increasingly moving towards approaches suitable for languages with minimal or no annotated resources. First, we survey recent developments in computational morphology with a focus on low-resource languages. Second, we argue that the field is ready to tackle the logical next challenge: understanding a language's morphology from raw text alone. We perform an empirical study on a truly unsupervised version of the paradigm completion task and show that, while existing state-of-the-art models bridged by two newly proposed models we devise perform reasonably, there is still much room for improvement. The stakes are high: solving this task will increase the language coverage of morphological resources by a number of magnitudes.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

—

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Findings of the Association for Computational Linguistics: ACL 2022

ISBN

978-1-955917-25-4

ISSN

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e-ISSN

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Počet stran výsledku

20

Strana od-do

988-1007

Název nakladatele

Association for Computational Linguistics

Místo vydání

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Místo konání akce

Dublin, Ireland

Datum konání akce

1. 1. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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