Multi-Parallel Corpus of North Levantine Arabic

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11210%2F23%3A10475890" target="_blank" >RIV/00216208:11210/23:10475890 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11320/23:10475890

Výsledek na webu

<a href="https://aclanthology.org/2023.arabicnlp-1.34/" target="_blank" >https://aclanthology.org/2023.arabicnlp-1.34/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.18653/v1/2023.arabicnlp-1.34" target="_blank" >10.18653/v1/2023.arabicnlp-1.34</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multi-Parallel Corpus of North Levantine Arabic

Popis výsledku v původním jazyce

Low-resource Machine Translation (MT) is characterized by the scarce availability of training data and/or standardized evaluation benchmarks. In the context of Dialectal Arabic, recent works introduced several evaluation benchmarks covering both Modern Standard Arabic (MSA) and dialects, mapping, however, mostly to a single Indo-European language - English. In this work, we introduce a multi-lingual corpus consisting of 120,600 multi-parallel sentences in English, French, German, Greek, Spanish, and MSA selected from the OpenSubtitles corpus, which were manually translated into the North Levantine Arabic. By conducting a series of training and fine-tuning experiments, we explore how this novel resource can contribute to the research on Arabic MT. We make the dataset publicly available at http://hdl.handle.net/11234/1-5033 for research purposes.

Název v anglickém jazyce

Multi-Parallel Corpus of North Levantine Arabic

Popis výsledku anglicky

Low-resource Machine Translation (MT) is characterized by the scarce availability of training data and/or standardized evaluation benchmarks. In the context of Dialectal Arabic, recent works introduced several evaluation benchmarks covering both Modern Standard Arabic (MSA) and dialects, mapping, however, mostly to a single Indo-European language - English. In this work, we introduce a multi-lingual corpus consisting of 120,600 multi-parallel sentences in English, French, German, Greek, Spanish, and MSA selected from the OpenSubtitles corpus, which were manually translated into the North Levantine Arabic. By conducting a series of training and fine-tuning experiments, we explore how this novel resource can contribute to the research on Arabic MT. We make the dataset publicly available at http://hdl.handle.net/11234/1-5033 for research purposes.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of ArabicNLP 2023

ISBN

978-1-959429-27-2

ISSN

—

e-ISSN

—

Počet stran výsledku

7

Strana od-do

411-417

Název nakladatele

Association for Computational Linguistics

Místo vydání

Stroudsburg, PA, USA

Místo konání akce

Singapore, Singapore

Datum konání akce

7. 12. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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