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
    • Design Thinking – February 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
    • Design Thinking – February 2021
    • — Divider —
    • SlatorCon Coverage
    • Other Events
  • Directory
  • RFP Center
  • Jobs

Advertise on Slator! Download the 2021 Online Media Kit Now

  • Slator Market Intelligence
  • Slator Advertising Services
  • Slator Advisory
  • Login
Search
Generic filters
Exact matches only
Advertisement
Neural Machine Translation Improving Fast, Study Finds

4 years ago

August 31, 2016

Neural Machine Translation Improving Fast, Study Finds

Academia ·

by Hazel Mae Pan

On August 31, 2016

4 years ago
Academia ·

by Hazel Mae Pan

On August 31, 2016

Neural Machine Translation Improving Fast, Study Finds

A study published on August 16, 2016 claims that Neural Machine Translation (NMT) outperforms phrase-based MT (PBMT) and provides better translations in the “particularly hard” to translate English-German language pair.

In the past, the researchers say, NMT was considered “too computationally costly and resource demanding” to compete with PBMT. Well, NMT literally need(ed) a lot of electricity. However, this has apparently changed beginning 2015, and NMT is now becoming more competitive.

The researchers (Luisa Bentivogli, Mauro Cettolo, and Marcello Federico of Fondazione Bruno Kessler, Trento Italy; Arianna Bisazza of the University of Amsterdam) found that, architecturally speaking, NMT is simpler than traditional statistical MT systems. Interestingly enough, however, they also add that the process is “less transparent” with NMT, saying that “the translation process is totally opaque to the analysis.” How NMT does what it does still seems a bit of a black box.

Advertisement

For the study, the researchers built on evaluation data from the IWSLT 2015 (International Workshop on Spoken Language Translation) MT English-German task and compared results using what they call the “first four top-ranking systems”; that is, NMT and three other phrase-based MT approaches.

Translate TED

The researchers sourced translation material from TED talks (transcripts translated from English into German), reasoning that the language used is structurally less complex, more conversational than formal, and required “a lower amount of rephrasing and reordering.”

As to why English and German, the researchers said using the two languages would be interesting because, despite belonging to the same language family, “they have marked differences in levels of inflection, morphological variation, and word order, especially long-range reordering of verbs.”

“The outcomes of the analysis confirm that NMT has significantly pushed ahead the state of the art”—Bentivogli, Cettolo, Federico, Bisazza

And it is in this aspect of better word reordering, particularly in the case of proper verb placement, that NMT shines. To quote, “one of the major strengths of the NMT approach is its ability to place German words in the right position even when this requires considerable reordering.”

Those Misplaced German Verbs

In contrast, the study indicated that “verbs are by far the most often misplaced word category in all PBMT systems,” which the researchers pointed out as a common problem affecting standard phrase-based statistical MT.

In summary, the outcome of the study’s analysis confirmed that NMT reduced the overall effort by a post-editor by 26% compared to PBMT output. In addition, NMT produced 70% less verb placement errors, 50% less word order errors, 19% less morphological errors, and 17% less lexical errors.

“Machine translation is definitely not a solved problem”—Bentivogli, Cettolo, Federico, Bisazza

However, despite outperforming PBMT systems on all sentence lengths, the performance of NMT degraded faster than its competitors the longer the input sentence became, which was one aspect the researchers singled out as an area for future work on improving NMT.

The researchers’ sense of excitement is palpable when they write “machine translation is definitely not a solved problem, but the time is finally ripe to tackle its most intricate aspects.”

TAGS

machine translationneural machine translationstatistical machine translation
SHARE
Hazel Mae Pan

By Hazel Mae Pan

Research Editor at Slator. Wide reader, online course consumer, computer science and transhumanism enthusiast, among other things. Bikes to work, so not a total couch potato.

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
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

Pro Guide: Sales and Marketing for Language Service Providers

Pro Guide: Sales and Marketing for Language Service Providers

by Slator

Press Releases

See all
Across Systems will be part of the Volaris Group

Across Systems will be part of the Volaris Group

by Across Systems GmbH

How Localex Made It Through the Pandemic

How Localex Made It Through the Pandemic

by Localex

Join Us for the First Virtual Together 2021 Next Month!

Join Us for the First Virtual Together 2021 Next Month!

by Elia

Upcoming Events

See All
  1. Handling Sensitive Information Webinar

    Handling Sensitive Calls with Limited English Proficient Consumers

    by Lionbridge

    · February 10

    Learn more about how Lionbridge Over-the-Phone Interpretation Services can help bridge communication gaps with limited...

    More info FREE

Featured Companies

See all
Text United

Text United

Memsource

Memsource

Wordbank

Wordbank

Protranslating

Protranslating

Seprotec

Seprotec

Versacom

Versacom

SDL

SDL

Smartling

Smartling

Lingotek

Lingotek

XTM International

XTM International

Smartcat

Smartcat

Translators without Borders

Translators without Borders

STAR Group

STAR Group

memoQ Translation Technologies

memoQ Translation Technologies

Advertisement

Popular articles

Why Netflix Shut Down Its Translation Portal Hermes

Why Netflix Shut Down Its Translation Portal Hermes

by Esther Bond

Top Language Industry Quotes of 2020

Top Language Industry Quotes of 2020

by Monica Jamieson

The Most Popular Language Industry Stories of 2020

The Most Popular Language Industry Stories of 2020

by Seyma Albarino

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 13,000 subscribers and get the latest language industry intelligence every Friday

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