logo image
  • News
    • People Moves
    • Deal Wins
    • Demand Drivers
    • M&A and Funding
    • Financial Results
    • Technology
    • Academia
    • Industry News
    • Features
    • Machine Translation
    • — Divider —
    • Slator Pro
    • — Divider —
    • Press Releases
    • Sponsored Content
  • Data & Research
    • Research Reports & Pro Guides
    • Language Industry Investor Map
    • Real-Time Charts of Listed LSPs
    • Language Service Provider Index
  • Podcasts & Videos
  • Events
    • SlatorCon Remote May 2021
    • Localizing at Scale for International Growth
    • Design Thinking May 2021
    • — Divider —
    • SlatorCon Coverage
    • Other Events
  • Directory
  • RFP Center
  • Jobs
MENU
  • News
    • People Moves
    • Deal Wins
    • Demand Drivers
    • M&A and Funding
    • Financial Results
    • Technology
    • Academia
    • Industry News
    • Features
    • Machine Translation
    • — Divider —
    • Slator Pro
    • — Divider —
    • Press Releases
    • Sponsored Content
  • Data & Research
    • Research Reports & Pro Guides
    • Language Industry Investor Map
    • Real-Time Charts of Listed LSPs
    • Language Service Provider Index
  • Podcasts & Videos
  • Events
    • SlatorCon Remote May 2021
    • Localizing at Scale for International Growth
    • Design Thinking May 2021
    • — Divider —
    • SlatorCon Coverage
    • Other Events
  • Directory
  • RFP Center
  • Jobs

Register Before April 15th for SlatorCon Remote and Save 15%!

  • Slator Market Intelligence
  • Slator Advertising Services
  • Slator Advisory
  • Login
Search
Generic filters
Exact matches only
Advertisement
Yes, Post-Editese Is Real, Study Finds

2 years ago

July 10, 2019

Yes, Post-Editese Is Real, Study Finds

Academia ·

by Florian Faes

On July 10, 2019

2 years ago
Academia ·

by Florian Faes

On July 10, 2019

Yes, Post-Editese Is Real, Study Finds

How does machine translation output post-edited by human linguists (PEMT) differ from translations from scratch; that is, translation produced without help or interference from a computer-generated first draft (HT)?

Three years into the age of neural machine translation, and as a significant portion of the language industry has transitioned to a post-editing-only world, this is a highly relevant question to explore.

In a paper entitled “Post-editese: an Exacerbated Translationese” published on July 1, 2019, University of Groningen Assistant Professor Antonio Toral said his “current research can be framed as a quest to find out whether there is evidence of post-editese.”

Advertisement

“I got interested back in 2014 in machine-assisted translation of literary texts (novels),” Toral told Slator. “I’ve previously conducted a post-editing experiment with professional literary translators and the results were positive in terms of productivity. However, I note that in that particular text type the reading experience is really important. Hence, I got interested in analyzing human vs post-edited translations. This paper is my first attempt at that.”

Slator 2020 Language Industry Market Report

Data and Research, Slator reports
55 pages. Total market size, biz dev and sales insights, TMS & MT review, buyer segment analysis, M&A, Covid impact & outlook.
$480 BUY NOW

In the paper, Toral conducted a set of computational analyses where he compared “PE against HT on three different datasets that cover five translation directions with measures that address different translation universals and laws of translation: simplification, normalisation and interference.”

Toral found that PEMT has lower lexical variety and lower lexical density. Furthermore, he found that the sentence length of PEMT corresponds more closely to that of the source text. In terms of part-of-speech (PoS) sequences, too, PEMT resembles the original more closely than HT.

It is no coincidence that Toral’s interest in the question arose in the context of literary translation, which lies at the outer edge of the spectrum of text types requiring a translator to take liberties. While neural machine translation has come a long way in producing fluent output, computers still lack the ability to rewrite, add, combine, or remove in the fundamentally creative way humans are able to.

Compared to unaided human translations, we show evidence that post-edited translations are simpler, more normalised and have more interference from the source language. Could post-editing then have a negative influence on the target language? If so, should we care about that? 1/2

— Antonio Toral (@_atoral) July 2, 2019

In a nutshell, the demonstrated productivity gains achieved by PEMT come at the cost of producing a translation that, according to the paper, “is simpler and more normalised and has a higher degree of interference from the source language than HT.”

Asked about potential limitations to keep in mind when reviewing his research, Toral commented: “One issue is that the metrics I have used are rather simple and work at surface level. I cannot say yet whether an analysis using more linguistically-oriented features (e.g., using syntactic information) would lead to the same results. Another issue is that the datasets are rather small; I hope with these results I’ll be able to convince someone in industry to use bigger datasets.”

Slator 2019 Neural Machine Translation Report: Deploying NMT in Operations

Data and Research
32 pages, NMT state-of-the-art, 5 case studies, 30 commentaries, NMT in day-to-day operations
$85 BUY NOW

TAGS

Antonio Toral Ruizmachine translationMTneural machine translationPEMTpost editingpost-edited machine translationpost-edited MTUniversity of Groningen
SHARE
Florian Faes

By Florian Faes

Co-Founder of Slator. Linguist, business developer, and mountain runner. Based in the beautiful lakeside city of Zurich, Switzerland.

Advertisement

SUBSCRIBE TO THE SLATOR WEEKLY

Language Industry Intelligence
In Your Inbox. Every Friday

SUBSCRIBE

SlatorSweepSlatorPro
ResearchRFP CENTER

PUBLISH

PRESS RELEASEDIRECTORY LISTING
JOB ADEVENT LISTING

Bespoke advisory including speaking, briefings and M&A

SLATOR ADVISORY
Advertisement

Featured Reports

See all
Pro Guide: Translation Pricing and Procurement

Pro Guide: Translation Pricing and Procurement

by Slator

Slator 2020 Language Industry M&A and Funding Report

Slator 2020 Language Industry M&A and Funding Report

by Slator

Slator 2021 Data-for-AI Market Report

Slator 2021 Data-for-AI Market Report

by Slator

Slator 2020 Medtech Translation and Localization Report

Slator 2020 Medtech Translation and Localization Report

by Slator

Press Releases

See all
Smartling Announces Smartling+

Smartling Announces Smartling+

by Smartling

XTM Cloud 12.7 “Intelligent Connectivity” is Here

XTM Cloud 12.7 “Intelligent Connectivity” is Here

by XTM International

LocHub Announces QA Localization Solution For Multilingual Content Publishing Processes

LocHub Announces QA Localization Solution For Multilingual Content Publishing Processes

by Xillio

Upcoming Events

See All
  1. T-Update-2021

    T-UPDATE ’21 VIRTUAL

    by Gerard Castañeda

    · April 15

    Join us at the leading language Industry event for decision-makers. Just pack your agenda for 2 days and travel to the...

    More info €65-421

Featured Companies

See all
Sunyu Transphere

Sunyu Transphere

Text United

Text United

Memsource

Memsource

Wordbank

Wordbank

Protranslating

Protranslating

SeproTec

SeproTec

Versacom

Versacom

Smartling

Smartling

XTM International

XTM International

Translators without Borders

Translators without Borders

STAR Group

STAR Group

memoQ Translation Technologies

memoQ Translation Technologies

Advertisement

Popular articles

Google Translate Not Ready for Use in Medical Emergencies But Improving Fast — Study

Google Translate Not Ready for Use in Medical Emergencies But Improving Fast — Study

by Seyma Albarino

The Slator 2021 Language Service Provider Index

The Slator 2021 Language Service Provider Index

by Slator

DeepL Adds 13 European Languages as Traffic Continues to Surge

DeepL Adds 13 European Languages as Traffic Continues to Surge

by Marion Marking

SlatorPod: The Weekly Language Industry Podcast

connect with us

footer logo

Slator makes business sense of the language services and technology market.

Our Company

  • Support
  • About us
  • Terms & Conditions
  • Privacy Policy

Subscribe to the Slator Weekly

Language Industry Intelligence
In Your Inbox. Every Friday

© 2021 Slator. All rights reserved.

Sign up to the Slator Weekly

Join over 13,800 subscribers and get the latest language industry intelligence every Friday

Your information will never be shared with third parties. No Spam.