UO @ HaSpeeDe2: Ensemble Model for Italian Hate Speech Detection (short paper)

Mariano Jason Rodriguez Cisnero, Reynier Ortega Bueno
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引用次数: 1

Abstract

English. This document describes our participation in the Hate Speech Detection task at Evalita 2020. Our system is based on deep learning techniques, specifically RNNs and attention mechanism, mixed with transformer representations and linguistic features. In the training process a multi task learning was used to increase the system effectiveness. The results show how some of the selected features were not a good combination within the model. Nevertheless, the generalization level achieved yield encourage results.
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UO @ HaSpeeDe2:意大利语仇恨语音检测的集成模型(短文)
英语。本文档描述了我们在Evalita 2020的仇恨言论检测任务中的参与情况。我们的系统基于深度学习技术,特别是rnn和注意机制,混合了转换表示和语言特征。在训练过程中,采用了多任务学习的方法来提高系统的有效性。结果表明,一些选择的特征在模型中不是一个很好的组合。然而,泛化水平取得了令人鼓舞的效果。
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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DIACR-Ita @ EVALITA2020: Overview of the EVALITA2020 Diachronic Lexical Semantics (DIACR-Ita) Task QMUL-SDS @ DIACR-Ita: Evaluating Unsupervised Diachronic Lexical Semantics Classification in Italian (short paper) By1510 @ HaSpeeDe 2: Identification of Hate Speech for Italian Language in Social Media Data (short paper) HaSpeeDe 2 @ EVALITA2020: Overview of the EVALITA 2020 Hate Speech Detection Task KIPoS @ EVALITA2020: Overview of the Task on KIParla Part of Speech Tagging
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