  In this paper we present ensemble-based systems for dialect and language
variety identification using the datasets made available by the organizers of
the VarDial Evaluation Campaign 2018. We present a system developed to
discriminate between Flemish and Dutch in subtitles and a system trained to
discriminate between four Arabic dialects: Egyptian, Levantine, Gulf, North
African, and Modern Standard Arabic in speech broadcasts. Finally, we compare
the performance of these two systems with the other systems submitted to the
Discriminating between Dutch and Flemish in Subtitles (DFS) and the Arabic
Dialect Identification (ADI) shared tasks at VarDial 2018.
