阿拉伯语细粒度方言识别的智能分类器

WANLP@ACL 2019 Pub Date : 2019-08-01 DOI:10.18653/v1/W19-4633

K. Meftouh, Karima Abidi, S. Harrat, K. Smaïli

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引用次数: 7

摘要

本文描述了SMarT研究组在阿拉伯语细粒度方言识别Madar共享任务框架下构建方言识别系统的方法。我们尝试了几种方法，但我们最终决定除了使用语言模型概率外，还使用基于单词和字符图的多项式朴素贝叶斯分类器。我们在宏观精度方面获得了67.73%的分数，宏观平均f1得分为67.31%

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The SMarT Classifier for Arabic Fine-Grained Dialect Identification

This paper describes the approach adopted by the SMarT research group to build a dialect identification system in the framework of the Madar shared task on Arabic fine-grained dialect identification. We experimented several approaches, but we finally decided to use a Multinomial Naive Bayes classifier based on word and character ngrams in addition to the language model probabilities. We achieved a score of 67.73% in terms of Macro accuracy and a macro-averaged F1-score of 67.31%

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WANLP@ACL 2019

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