Twist Bytes - German Dialect Identification with Data Mining Optimization

Fernando Benites, Ralf Grubenmann, Pius von Däniken, Dirk von Grünigen, Jan Deriu, Mark Cieliebak


Abstract
We describe our approaches used in the German Dialect Identification (GDI) task at the VarDial Evaluation Campaign 2018. The goal was to identify to which out of four dialects spoken in German speaking part of Switzerland a sentence belonged to. We adopted two different meta classifier approaches and used some data mining insights to improve the preprocessing and the meta classifier parameters. Especially, we focused on using different feature extraction methods and how to combine them, since they influenced very differently the performance of the system. Our system achieved second place out of 8 teams, with a macro averaged F-1 of 64.6%.
Anthology ID:
W18-3925
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:
218–227
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URL:
https://aclanthology.org/W18-3925
DOI:
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Cite (ACL):
Fernando Benites, Ralf Grubenmann, Pius von Däniken, Dirk von Grünigen, Jan Deriu, and Mark Cieliebak. 2018. Twist Bytes - German Dialect Identification with Data Mining Optimization. In Proceedings of the Fifth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial 2018), pages 218–227, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
Cite (Informal):
Twist Bytes - German Dialect Identification with Data Mining Optimization (Benites et al., 2018)
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PDF:
https://aclanthology.org/W18-3925.pdf