@inproceedings{bulte-tezcan-2019-neural,
title = "Neural Fuzzy Repair: Integrating Fuzzy Matches into Neural Machine Translation",
author = "Bulte, Bram and
Tezcan, Arda",
editor = "Korhonen, Anna and
Traum, David and
M{\`a}rquez, Llu{\'\i}s",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P19-1175",
doi = "10.18653/v1/P19-1175",
pages = "1800--1809",
abstract = "We present a simple yet powerful data augmentation method for boosting Neural Machine Translation (NMT) performance by leveraging information retrieved from a Translation Memory (TM). We propose and test two methods for augmenting NMT training data with fuzzy TM matches. Tests on the DGT-TM data set for two language pairs show consistent and substantial improvements over a range of baseline systems. The results suggest that this method is promising for any translation environment in which a sizeable TM is available and a certain amount of repetition across translations is to be expected, especially considering its ease of implementation.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="bulte-tezcan-2019-neural">
<titleInfo>
<title>Neural Fuzzy Repair: Integrating Fuzzy Matches into Neural Machine Translation</title>
</titleInfo>
<name type="personal">
<namePart type="given">Bram</namePart>
<namePart type="family">Bulte</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Arda</namePart>
<namePart type="family">Tezcan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2019-07</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics</title>
</titleInfo>
<name type="personal">
<namePart type="given">Anna</namePart>
<namePart type="family">Korhonen</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">David</namePart>
<namePart type="family">Traum</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Lluís</namePart>
<namePart type="family">Màrquez</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Florence, Italy</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>We present a simple yet powerful data augmentation method for boosting Neural Machine Translation (NMT) performance by leveraging information retrieved from a Translation Memory (TM). We propose and test two methods for augmenting NMT training data with fuzzy TM matches. Tests on the DGT-TM data set for two language pairs show consistent and substantial improvements over a range of baseline systems. The results suggest that this method is promising for any translation environment in which a sizeable TM is available and a certain amount of repetition across translations is to be expected, especially considering its ease of implementation.</abstract>
<identifier type="citekey">bulte-tezcan-2019-neural</identifier>
<identifier type="doi">10.18653/v1/P19-1175</identifier>
<location>
<url>https://aclanthology.org/P19-1175</url>
</location>
<part>
<date>2019-07</date>
<extent unit="page">
<start>1800</start>
<end>1809</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Neural Fuzzy Repair: Integrating Fuzzy Matches into Neural Machine Translation
%A Bulte, Bram
%A Tezcan, Arda
%Y Korhonen, Anna
%Y Traum, David
%Y Màrquez, Lluís
%S Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
%D 2019
%8 July
%I Association for Computational Linguistics
%C Florence, Italy
%F bulte-tezcan-2019-neural
%X We present a simple yet powerful data augmentation method for boosting Neural Machine Translation (NMT) performance by leveraging information retrieved from a Translation Memory (TM). We propose and test two methods for augmenting NMT training data with fuzzy TM matches. Tests on the DGT-TM data set for two language pairs show consistent and substantial improvements over a range of baseline systems. The results suggest that this method is promising for any translation environment in which a sizeable TM is available and a certain amount of repetition across translations is to be expected, especially considering its ease of implementation.
%R 10.18653/v1/P19-1175
%U https://aclanthology.org/P19-1175
%U https://doi.org/10.18653/v1/P19-1175
%P 1800-1809
Markdown (Informal)
[Neural Fuzzy Repair: Integrating Fuzzy Matches into Neural Machine Translation](https://aclanthology.org/P19-1175) (Bulte & Tezcan, ACL 2019)
ACL