基于变压器的英语和斯洛文尼亚语讽刺检测

Proceedings of the 2021 7th Student Computer Science Research Conference (StuCoSReC) Pub Date : 2021-09-13 DOI:10.18690/978-961-286-516-0.10

Matic Rašl, Mitja Zalik, Vid Keršič

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引用次数: 0

摘要

讽刺检测是自然语言处理领域的一个重要问题。在本文中，我们比较了三种神经网络在英语和斯洛文尼亚语数据集上的讽刺检测性能。每个网络都基于一个异变模型:RoBERTa、蒸馏器-伯特和蒸馏器-多语言。除了现有的基于twitter的英语数据集之外，我们还使用相同的方法创建了斯洛文尼亚语数据集。英语和斯洛文尼亚语数据集的F1得分分别为0.72和0.88。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Transformer-based Sarcasm Detection in English and Slovene Language

Sarcasm detection is an important problem in the field of natural language processing. In this pa-per, we compare performances of the three neural networks for sarcasm detection on English and Slovene datasets. Each network is based on a di˙erent transformer model: RoBERTa, Distil-Bert, and DistilBert – multilingual. In addition to the existing Twitter-based English dataset, we also created the Slovene dataset using the same approach. An F1 score of 0.72 and 0.88 was achieved in the English and Slovene dataset, re-spectively.

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Proceedings of the 2021 7th Student Computer Science Research Conference (StuCoSReC)

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