@inproceedings{hebenstreit-2022-post,
title = "Post-editing of Machine-Translated Patents: High Tech with High Stakes",
author = "Hebenstreit, Aaron",
editor = "Campbell, Janice and
Larocca, Stephen and
Marciano, Jay and
Savenkov, Konstantin and
Yanishevsky, Alex",
booktitle = "Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track)",
month = sep,
year = "2022",
address = "Orlando, USA",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2022.amta-upg.3",
pages = "24--31",
abstract = "Ever-improving quality in MT makes it increasingly difficult for users to identify errors, sometimes obvious and other times subtle but treacherous, such as in patents and IP. Linguists, developers, and other {``}humans in the loop{''} should be ready to adapt their approaches to checking technical translations for accuracy. In this talk, real-world Chinese-to-English patent translations will be used in side-by-side comparisons of raw MT output and courtroom-ready products. The types of issues that can make or break a post-edited translation will be illustrated, with discussion of the principles underlying the error types. Certain nuances that challenge both humans and machines must be revealed in order to create a translation product that withstands the scrutiny of the attorneys, scientists, and inventors who might procure it. This talk will explore the nature of error detection and classification when reviewing patent texts translated by humans, computers, or a combination thereof.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="hebenstreit-2022-post">
<titleInfo>
<title>Post-editing of Machine-Translated Patents: High Tech with High Stakes</title>
</titleInfo>
<name type="personal">
<namePart type="given">Aaron</namePart>
<namePart type="family">Hebenstreit</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2022-09</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Janice</namePart>
<namePart type="family">Campbell</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Stephen</namePart>
<namePart type="family">Larocca</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jay</namePart>
<namePart type="family">Marciano</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Konstantin</namePart>
<namePart type="family">Savenkov</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alex</namePart>
<namePart type="family">Yanishevsky</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Machine Translation in the Americas</publisher>
<place>
<placeTerm type="text">Orlando, USA</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Ever-improving quality in MT makes it increasingly difficult for users to identify errors, sometimes obvious and other times subtle but treacherous, such as in patents and IP. Linguists, developers, and other “humans in the loop” should be ready to adapt their approaches to checking technical translations for accuracy. In this talk, real-world Chinese-to-English patent translations will be used in side-by-side comparisons of raw MT output and courtroom-ready products. The types of issues that can make or break a post-edited translation will be illustrated, with discussion of the principles underlying the error types. Certain nuances that challenge both humans and machines must be revealed in order to create a translation product that withstands the scrutiny of the attorneys, scientists, and inventors who might procure it. This talk will explore the nature of error detection and classification when reviewing patent texts translated by humans, computers, or a combination thereof.</abstract>
<identifier type="citekey">hebenstreit-2022-post</identifier>
<location>
<url>https://aclanthology.org/2022.amta-upg.3</url>
</location>
<part>
<date>2022-09</date>
<extent unit="page">
<start>24</start>
<end>31</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Post-editing of Machine-Translated Patents: High Tech with High Stakes
%A Hebenstreit, Aaron
%Y Campbell, Janice
%Y Larocca, Stephen
%Y Marciano, Jay
%Y Savenkov, Konstantin
%Y Yanishevsky, Alex
%S Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track)
%D 2022
%8 September
%I Association for Machine Translation in the Americas
%C Orlando, USA
%F hebenstreit-2022-post
%X Ever-improving quality in MT makes it increasingly difficult for users to identify errors, sometimes obvious and other times subtle but treacherous, such as in patents and IP. Linguists, developers, and other “humans in the loop” should be ready to adapt their approaches to checking technical translations for accuracy. In this talk, real-world Chinese-to-English patent translations will be used in side-by-side comparisons of raw MT output and courtroom-ready products. The types of issues that can make or break a post-edited translation will be illustrated, with discussion of the principles underlying the error types. Certain nuances that challenge both humans and machines must be revealed in order to create a translation product that withstands the scrutiny of the attorneys, scientists, and inventors who might procure it. This talk will explore the nature of error detection and classification when reviewing patent texts translated by humans, computers, or a combination thereof.
%U https://aclanthology.org/2022.amta-upg.3
%P 24-31
Markdown (Informal)
[Post-editing of Machine-Translated Patents: High Tech with High Stakes](https://aclanthology.org/2022.amta-upg.3) (Hebenstreit, AMTA 2022)
ACL