Our ELG project OPUS-MT is mentioned in the IEEE Spectrum post on machine translation within the European Language Grid:

Another early-stage project is coming from Jörg Tiedemann at the University of Helsinki, who is working with colleagues to develop open translation models for the Grid. These models use deep neural networks—layered software architectures that implement complex mathematical functions—to map text into numeric representations. Using data sets to train the models to find the best ways to solve problems takes a lot of computing power and is expensive. Making the models available for re-use will help developers build tools for low-density languages. “Minority languages get too little attention because they are not commercially interesting,” Tiedemann says. “This gap needs to be closed.”

22 open positions at FCAI

Are you an ambitious researcher looking for an interesting postdoc, research fellow or PhD position?

The Finnish Center for Artificial Intelligence FCAI offers a possibility for 22 new researchers to join a unique research community with an attractive joint mission. Especially interesting for NLP researchers: Topic 11: Interactive AI using multimodal communication

FCAI welcomes applicants with diverse backgrounds, and qualified female candidates are explicitly encouraged to apply. The deadline for applications is October 5, 2020 (midnight UTC+02:00). Read more and apply here: https://fcai.fi/we-are-hiring

Public PhD defence on May, 28: Tommi Jauhiainen

Tommi Jouhiainen is defending his PhD thesis in language technology on “Language Identification in Texts” on Tuesday, May, 28 at 12 in auditorio XII in the main building of the university. The thesis is available at http://urn.fi/URN:ISBN:978-951-51-5131-5 and the opponent is Nikola Ljubešić from the Jožef Stefan Institute in Ljubljana and the University of Zagreb.

University of Helsinki Language Technology group successful at WMT18 machine translation tasks

Our research group successfully participated in this year’s WMT machine translation tasks, taking the shared first place in both the English-Finnish and Finnish-English news translation tasks.

Shared Task: Machine Translation of News

We also participated in the Multimodal Machine Translation task as part of the MeMaD project, taking the first place in English-German and in English-French translation.

Shared Task: Multimodal Machine Translation En-De

In both the news and multimodal translation tasks, the best systems from the Language Technology group utilised state-of-the-art neural machine translation models.

System papers describing the models will be presented at EMNLP 2018 Third Conference on Machine Translation (WMT18) later this year.

Shared Task: Multimodal Machine Translation En-Fr

Congratulations to our team!