Multilingual Auxiliary Tasks Training: Bridging the Gap between
Languages for Zero-Shot Transfer of Hate Speech Detection Models
- URL: http://arxiv.org/abs/2210.13029v2
- Date: Tue, 25 Oct 2022 08:20:35 GMT
- Title: Multilingual Auxiliary Tasks Training: Bridging the Gap between
Languages for Zero-Shot Transfer of Hate Speech Detection Models
- Authors: Syrielle Montariol, Arij Riabi, Djam\'e Seddah
- Abstract summary: We show how hate speech detection models benefit from a cross-lingual knowledge proxy brought by auxiliary tasks fine-tuning.
We propose to train on multilingual auxiliary tasks to improve zero-shot transfer of hate speech detection models across languages.
- Score: 3.97478982737167
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Zero-shot cross-lingual transfer learning has been shown to be highly
challenging for tasks involving a lot of linguistic specificities or when a
cultural gap is present between languages, such as in hate speech detection. In
this paper, we highlight this limitation for hate speech detection in several
domains and languages using strict experimental settings. Then, we propose to
train on multilingual auxiliary tasks -- sentiment analysis, named entity
recognition, and tasks relying on syntactic information -- to improve zero-shot
transfer of hate speech detection models across languages. We show how hate
speech detection models benefit from a cross-lingual knowledge proxy brought by
auxiliary tasks fine-tuning and highlight these tasks' positive impact on
bridging the hate speech linguistic and cultural gap between languages.
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