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.
Microsoft’s NTREX-128, the second largest human-translated test set, is another benchmark for the evaluation of massively multilingual machine translation research.
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.
EU’s DG CONNECT awards a EUR 8m contract to create a platform and marketplace for multilingual language data sharing and exchange.
The global language industry remained surprisingly resilient in 2022, with nine CEO appointments at language services and tech providers as well as several C-level and VP hires, as reported by Slator.
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.
All you need to know about how you score against postediting translation speed standards and the factors affecting your performance.
European Society for Translation Studies names three projects with the greatest potential impact on the field, awarding them the 2022 Translation Prize.
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.
Meta has released SpeechMatrix, a large-scale mined corpus of multilingual speech-to-speech translations.
Experts in language technology from ADAPT urge European Parliament to support language equality and prevent digital extinction of minority languages.
BNP Paribas, Europe’s second largest bank, applies domain adaptation for multilingual neural machine translation models — without excessive loss of knowledge across language pairs.
The European Master’s in Translation competence framework has been updated and aims to best equip future translation graduates and increase their employability across Europe.
Large companies require translators to have core disciplinary knowledge, strong technical, intra- and interpersonal skills to remain competitive in the job market.
Snapshot of the most interesting language technology highlights from the latest edition of the State of AI Report compiled by a group of venture capitalists and researchers.
Researchers from Meta suggest training-data curation as a means to reduce added toxicity in machine translation. Toxicity categories include profanity, insults, hate speech, bullying, etc.
Researchers from Amazon present a simple procedure for extending pretrained machine translation evaluation metrics to the document level.
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.
NeTTT conference brings together academia, industry, and EU institutions, highlights new trends in translation and technology.
UN interpreters blame technology for the decline in their working conditions. But the benefits of technology are real and should not be ignored by the interpreting community.
Cohere, OpenAI, and AI21 Labs publish preliminary set of best practices applicable to any organization developing or deploying large language models.