No Post-Editing Output: Microsoft Releases Massive Machine Translation Test Set
Microsoft’s NTREX-128, the second largest human-translated test set, is another benchmark for the evaluation of massively multilingual machine translation research.
MT
A Realistic Dataset for Evaluating Gender Bias in Machine Translation by Amazon
Amazon releases MT-GenEval, a realistic dataset for evaluating gender bias in machine translation, to better understand how MT models perform on gender translation accuracy.
Revisiting Controlled Language for Better Machine Translation Quality
Researchers revisit controlled language as a means of improving MT quality. A new methodology based on stylistic quality is said to eliminate repeated fine tuning.
Working Around Machine Translation’s Need for Large-Scale Training Data
Unlike some fields in machine learning, machine translation still requires large sets of training data. The solution? Creating more data when none (or not enough) exists.
Smartling’s Bryan Murphy on How Translation Creates Growth as Budgets Become Tight
At SlatorCon Remote December 2022, Bryan Murphy, CEO of Smartling, talks about leveraging AI and automation to drive growth and reduce costs in the event of a recession.
Slator 2022 Language Industry M&A and Funding Report
44-pages on 2022 translation and localization industry acquisitions and translation startup investments, with valuations, deal rationale.
Intento CEO Outlines Seven Stages of Machine Translation Adoption
At SlatorCon Remote December 2022, Konstantin Savenkov, CEO at Intento, on machine translation bottlenecks, value drivers, ROI, and the future of the global language market.
How Fast Can You Post-Edit Machine Translation?
All you need to know about how you score against postediting translation speed standards and the factors affecting your performance.
Reader Polls: Should Language Service Providers Diversify Beyond Translation?
LSPs think of diversification, DeepL retains its edge after five years, cultural neutralization of source marketing language, automatic transcription far from general adoption.
How Good Are Large Language Models at Machine Translation?
Very fluent but not yet highly accurate — this is how Google researchers describe machine translation performance of large language models versus state-of-the-art MT.
How Europe’s Second Largest Bank Built Multilingual Machine Translation In-House
BNP Paribas, Europe’s second largest bank, applies domain adaptation for multilingual neural machine translation models — without excessive loss of knowledge across language pairs.
In Literary Translation, Humans Prefer Humans and Machines Prefer Machines
A literary translation experiment using Google Translate and paragraph alignment reveals only slight improvements in post-edited text versus professional human translations.
Converting Any Pre-Trained MT Metric Into a Document-Level Metric — An Amazon Study
Researchers from Amazon present a simple procedure for extending pretrained machine translation evaluation metrics to the document level.
Why Quality Estimation Should Be Fundamental to Machine Translation
What you need to know about machine translation quality estimation (MTQE) — from benefits and challenges to industry adoption — as discussed by Adam Bittlingmayer and Conchita Laguardia.
Researchers Experiment With Machine Translation to Simplify Medical Language
When researchers experimented with machine translation to simplify medical content for patients, the results were mixed but promising.
Indian Machine Dubbing Startup Dubdub Raises USD 1m
Machine dubbing startup, Dubdub, raises USD 1m in seed funding. Finds traction with marketing, creative agencies; sees “strong pull” from production houses, OTT.
DeepL in Hiring Spree as Machine Translation Juggernaut Takes on Localization Industry
An analysis of 300+ LinkedIn profiles associated with DeepL suggest the world's fastest-growing MT company has set its sights on enterprise localization and language services customers.
Can Machine Translation Facilitate Better Global Meetings in a Common Language?
Computer researchers at the University of Maryland experiment with machine translation to show how global meetings can be optimized.
AI Writing: Threat or Opportunity for Language Service Providers?
Natural language generation (NLG) startups can help content creators write copy in multiple languages. But are AI writers a threat or an opportunity for LSPs?
Automating Subtitling, Dubbing, Live Captioning With XL8 CEO Tim Jung
XL8 CEO, Tim Jung, on using machine translation and expert-in-the-loop AI technology for media localization and live events.
Neur.on Raises USD 1.6m to Scale TMS ‘Hyper-Specialized’ for Legal and Finance
Swiss SaaS platform, Neur.on, designed for localization users, buyers in legal and finance sectors, announces USD 1.6m investment round.
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