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ASIREM Participation at the Discriminating Similar Languages Shared Task 2016

2016-12-01WS 2016Unverified0· sign in to hype

Wafia Adouane, Nasredine Semmar, Richard Johansson

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Abstract

This paper presents the system built by ASIREM team for the Discriminating between Similar Languages (DSL) Shared task 2016. It describes the system which uses character-based and word-based n-grams separately. ASIREM participated in both sub-tasks (sub-task 1 and sub-task 2) and in both open and closed tracks. For the sub-task 1 which deals with Discriminating between similar languages and national language varieties, the system achieved an accuracy of 87.79\% on the closed track, ending up ninth (the best results being 89.38\%). In sub-task 2, which deals with Arabic dialect identification, the system achieved its best performance using character-based n-grams (49.67\% accuracy), ranking fourth in the closed track (the best result being 51.16\%), and an accuracy of 53.18\%, ranking first in the open track.

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