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”

Posters:

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

Demos:

  • 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”

FCAI Research Insight Event May 6, 2019

FCAI hosted Research Insight Event at Aalto university. The purpose of the day was to bring together FCAI’s academics and partners to discuss shared problems and to workshop future research ideas for the center.

Found in translation (FoTran) was presented by Jörg Tiedemann.
“Natural Language Processing is not only an important component of intelligent systems that interact with users but also develops into a core discipline of AI that aims at learning world knowledge from human communication. The goal of our research is to use translations to pick up essential semantics of natural language. Combining multilingual signals with multimodal grounding we aim at improved models for natural language understanding.”