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

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University of Helsinki Language Technology group at NoDaLiDa 2019

The University of Helsinki Language Technology group has a number of papers at The 22nd Nordic Conference on Computational Linguistics (NoDaLiDa’19). Here’s where you can find us. See you in Turku!

Monday September 30:

NLP4CALL workshop:

  • 13:15. Mathias Creutz, Eetu Sjöblom: “Toward automatic improvement of language produced by non-native language learners”

Constraint Grammar – Methods, Tools, and Applications workshop:

  • 14:15. Anssi Yli-Jyrä: “Constraint Grammar Is a Hand-Crafted Transformer”

Tuesday 01 October:

Oral presentations:
Parallel session B: Morphology and Syntax.

  • 13:45. Ilmari Kylliäinen and Miikka Silfverberg: “Ensembles of Neural Morphological Inflection Models”


  • 16:45. Jeff Ens, Mika Hämäläinen, Jack Rueter and Philippe Pasquier: “Morphosyntactic Disambiguation in an Endangered Language Setting”


  • 16:45. Mikko Aulamo and Jörg Tiedemann: “The OPUS Resource Repository: An Open Package for Creating Parallel Corpora and Machine Translation Services”

Wednesday 02 October

Oral presentations:
Parallel session B: Speech.

  • 14:50. Aarne Talman, Antti Suni, Hande Celikkanat, Sofoklis Kakouros, Jörg Tiedemann and Martti Vainio: “Predicting Prosodic Prominence from Text with Pre-trained Contextualized Word Representations”