Veronika Laippala
Turku Institute for Advanced Studies / School of Languages and Translation Studies, University of Turku, Finland
Jenna Kanerv
Department of Information Technology, University of Turku, Finland
Anna Missilä
School of Languages and Translation Studies, University of Turku, Finland
Sampo Pyysalo
Department of Information Technology, University of Turku, Finland
Tapio Salakoski
Department of Information Technology, University of Turku, Finland
Filip Ginter
Department of Information Technology, University of Turku, Finland
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Published in: Proceedings of the 20th Nordic Conference of Computational Linguistics, NODALIDA 2015, May 11-13, 2015, Vilnius, Lithuania
Linköping Electronic Conference Proceedings 109:15, p. 107-116
NEALT Proceedings Series 23:15, p. 107-116
This paper presents the first results on detecting informality, machine and human translations in the Finnish Internet Parsebank, a project aiming at a large-scale, web-based corpus with full morphological and syntactic analyses. The paper aims at classifying the Parsebank according to these criteria using syntactic n-grams, as well as studying the linguistic characteristics of the classes. The results are practically applicable, with an AUC range of 85–85% for the human, ~ 98% for the machine translated texts and 73% for the informal texts. While word-based classification performs well for the in-domain experiments, delexicalized methods with with morpho-syntactic features prove to be more tolerant to variation caused by genre or source language. In addition, the results show that the features used in the classification provide interesting pointers for further, more detailed studies on the linguistic characteristics of these texts.
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