Evaluating Pre-training Objectives for Low-Resource Translation into Morphologically Rich Languages

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A9EZYNSBS" target="_blank" >RIV/00216208:11320/22:9EZYNSBS - isvavai.cz</a>

Result on the web

<a href="https://aclanthology.org/2022.lrec-1.527" target="_blank" >https://aclanthology.org/2022.lrec-1.527</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Evaluating Pre-training Objectives for Low-Resource Translation into Morphologically Rich Languages

Original language description

The scarcity of parallel data is a major limitation for Neural Machine Translation (NMT) systems, in particular for translation into morphologically rich languages (MRLs). An important way to overcome the lack of parallel data is to leverage target monolingual data, which is typically more abundant and easier to collect. We evaluate a number of techniques to achieve this, ranging from back-translation to random token masking, on the challenging task of translating English into four typologically diverse MRLs, under low-resource settings. Additionally, we introduce Inflection Pre-Training (or PT-Inflect), a novel pre-training objective whereby the NMT system is pre-trained on the task of re-inflecting lemmatized target sentences before being trained on standard source-to-target language translation. We conduct our evaluation on four typologically diverse target MRLs, and find that PT-Inflect surpasses NMT systems trained only on parallel data. While PT-Inflect is outperformed by back-translation overall, combining the two techniques leads to gains in some of the evaluated language pairs.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

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

Project

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Continuities

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Publication year

2022

Confidentiality

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

Article name in the collection

Proceedings of the Thirteenth Language Resources and Evaluation Conference

ISBN

979-10-95546-72-6

ISSN

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e-ISSN

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Number of pages

11

Pages from-to

4933-4943

Publisher name

European Language Resources Association

Place of publication

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Event location

Marseille, France

Event date

Jan 1, 2022

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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