Kroon, Martin

Medvedeva, Masha

Plank, Barbara

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

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

https://pure.itu.dk/ws/files/83200513/DFS_2018.pdf

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

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