Brief personal and contact information for Stig-Arne Grönroos

M.Sc.(Tech.), Doctoral Student
Stig-Arne Grönroos
IRC nick
Waino (networks: IRCnet, quakenet, PirateNet)
Github
Waino
Email
firstname.lastname@​aalto.fi (name includes hyphen, but not dots on 'ö')
Phone
(+358) 40 739 8282
Office
Room G335 in Electrical Engineering Building, Otakaari 5, Otaniemi campus area, Espoo, Finland

The preferred ways to contact me are by IRC (casual) or email.

Employment and professional interests

I am currently a Doctoral Student at Aalto University School of Electrical Engineering, Department of Signal Processing and Acoustics.

My research topic is applying statistical morphology to machine translation into morphologically complex languages. I'm a part of the team working on Morfessor, a machine learning tool for morphological segmentation of natural language text.

My main professional interests are machine translation, natural language processing and machine learning. I'm also interested in active learning, data visualization, and recurrent neural networks.

Education

Diplomi-insinööri / Master of Science (Tech.) 2014
Aalto University School of Science
  • Major: Information and Computer Science
  • The degree was completed with distinction
Bachelor of Science (Tech.) 2012
Aalto University School of Science
Matriculation Examination 2004
Gymnasiet Lärkan

Publications

2016
Grönroos, S.-A., Virpioja, S., and Kurimo, M. (2016).
Hybrid Morphological Segmentation for Phrase-Based Machine Translation. In proceedings of the First Conference on Machine Translation.
Ruokolainen, T., Kohonen, O., Sirts, K., Grönroos, S.-A., Kurimo, M. and Virpioja, S. (2016).
A comparative study on minimally supervised morphological segmentation. Computational Linguistics.
2015
Grönroos, S.-A., Virpioja, S., and Kurimo, M. (2015).
Tuning Phrase-Based Segmented Translation for a Morphologically Complex Target Language. In proceedings of the Tenth Workshop on Statistical Machine Translation.
Virpioja, S. and Grönroos, S.-A. (2015).
LeBLEU: N-gram-based Translation Evaluation Score for Morphologically Complex Languages. In proceedings of the Tenth Workshop on Statistical Machine Translation.
Grönroos, S.-A., Jokinen, K., Hiovain, K., Kurimo, M., and Virpioja, S. (2015).
Low-Resource Active Learning of North Sámi Morphological Segmentation. In proceedings of the 1st International Workshop on Computational Linguistics for Uralic Languages.
2014
Grönroos, S.-A., Virpioja, S., Smit, P., and Kurimo, M. (2014).
Morfessor FlatCat: An HMM-based method for unsupervised and semi-supervised learning of morphology. In proceedings of the 25th International Conference on Computational Linguistics.
Smit, P., Virpioja, S., Grönroos, S.-A., and Kurimo, M. (2014).
Morfessor 2.0: Toolkit for statistical morphological segmentation. In 14th Conference of the European Chapter of the Association for Computational Linguistics. Software Demonstration.
Grönroos, S.-A. (2014).
Semi-supervised induction of a concatenative morphology with simple morphotactics. Master’s thesis, Department of Information and Computer Science, Aalto University, Espoo, Finland.
2013
Virpioja, S., Smit, P., Grönroos, S.-A., and Kurimo, M. (2013).
Morfessor 2.0: Python implementation and extensions for Morfessor Baseline. Report 25/2013 in Aalto University publication series SCIENCE + TECHNOLOGY, Department of Signal Processing and Acoustics, Aalto University.
2010
Grönroos, S.-A. (2010).
Parallelliserad klassifikation av dokumentsamling med hjälp av MapReduce. Bachelor’s thesis, Department of Information and Computer Science, Aalto University, Espoo, Finland.