Slator Pro Guide: Translation AI
The Slator Pro Guide: Translation AI is a vital and concise guide to applying large language models (LLMs) in translation workflows, featuring 10 practical use cases.
*New* Slator Pro Guide: Scaling an LSP Key Account — Growing Small Clients into Key Accounts
machine translation
How SignBank+ Improves Multilingual Sign-to-Spoken Language Machine Translation
Sign-to-spoken language machine translation research using a purpose-built dataset and an intermediate notation system reveals improvements in multilingual target text outputs.
Can Large Language Models Do Simultaneous Machine Translation?
Monash University researchers show that large language models can do real-time machine translation and propose new ways for model fine-tuning.
Speech Wikimedia Drops a 200GB Audio Dataset to Train ASR and Speech Translation
Researchers from NVIDIA, Factored.ai, Talon Voice, and others open-source a properly licensed dataset of 1,780 hours of speech in 77 different languages, plus transcriptions.
YouTube Launches a Multilingual Health Video Creator Program Using Machine Dubbing
YouTube Health launches THE-IQ Creator Program for healthcare video creators in four countries, including financing and pilot-phase access to the Aloud machine dubbing tool.
After Gizmodo Fires Spanish Writers, Google Now Ranks Raw Machine Translation
G/O Media fires Gizmodo’s entire staff of Spanish writers and begins publishing raw machine-translated versions of English articles that are now being indexed by Google Search.
DeepMind’s Path to Better Large Language Models Runs Through Machine Translation
DeepMind introduces a new method to improve the quality of large language models. Researchers choose machine translation as a use case to show how well the new approach works.
Top Language AI Researchers Propose New Way to Auto-Evaluate Machine Translation
Language AI researchers show that fine-tuning large language models with fine-grained human judgment data boosts machine translation evaluation.
New Trends in Machine Translation with Large Language Models by Longyue Wang
Longyue Wang on Tencent's approach to language technology and his research on the potential of large language models in more context-aware and personalized machine translation.
ADAPT Enhances Explainable Neural Machine Translation with adaptNMT
ADAPT researchers introduce adaptNMT, an innovative open-source application designed to simplify the development and deployment of machine translation models.
15 US Attorneys General Object to Human-Free Machine Translation of Emergency Alerts
Federal Communications Commission’s proposal to expand language access is a good start, officials from 15 states say, but should include (human) translation into 25 languages.
Ghent University’s MATEO Project Improves Access to Machine Translation Evaluation
MATEO aims to open up machine translation evaluation, making it accessible to more stakeholders and facilitating research, education, and critical evaluation of machine translation.
Research Shows How to Replicate ‘Translator Style’ in Literary Machine Translation
Boğaziçi University researchers reveal the potential of customizing MT systems to replicate a translator's style, leading to literary translations that mirror the translator's unique style.
Researchers Call for Clear Policies around Machine Translation Use in Higher Education
A paper discussing the use of digital tools in academia addresses machine translation as both a problematic and beneficial tool, proposing increased awareness and clear policies for its use.
This University Project Supports Post-Editing Training in Translator Education
The Post-Edit Me! project supports educators in developing innovative post-editing training practices, fostering enhanced post-editing skills for the future of the industry.
Your information will not be shared with third parties. No Spam.