When Simple n-gram Models Outperform Syntactic Approaches: Discriminating between Dutch and Flemish

Martin Kroon, Masha Medvedeva, Barbara Plank


Abstract
In this paper we present the results of our participation in the Discriminating between Dutch and Flemish in Subtitles VarDial 2018 shared task. We try techniques proven to work well for discriminating between language varieties as well as explore the potential of using syntactic features, i.e. hierarchical syntactic subtrees. We experiment with different combinations of features. Discriminating between these two languages turned out to be a very hard task, not only for a machine: human performance is only around 0.51 F1 score; our best system is still a simple Naive Bayes model with word unigrams and bigrams. The system achieved an F1 score (macro) of 0.62, which ranked us 4th in the shared task.
Anthology ID:
W18-3928
Volume:
Proceedings of the Fifth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial 2018)
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico, USA
Venues:
COLING | VarDial | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
244–253
Language:
URL:
https://www.aclweb.org/anthology/W18-3928
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/W18-3928.pdf