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Hits 1 – 2 of 2
1
Multilingual and Multimodal Abuse Detection ...
Sharon, Rini
;
Shah, Heet
;
Mukherjee, Debdoot
;
Gupta, Vikram
. - : arXiv, 2022
Abstract:
The presence of abusive content on social media platforms is undesirable as it severely impedes healthy and safe social media interactions. While automatic abuse detection has been widely explored in textual domain, audio abuse detection still remains unexplored. In this paper, we attempt abuse detection in conversational audio from a multimodal perspective in a multilingual social media setting. Our key hypothesis is that along with the modelling of audio, incorporating discriminative information from other modalities can be highly beneficial for this task. Our proposed method, MADA, explicitly focuses on two modalities other than the audio itself, namely, the underlying emotions expressed in the abusive audio and the semantic information encapsulated in the corresponding textual form. Observations prove that MADA demonstrates gains over audio-only approaches on the ADIMA dataset. We test the proposed approach on 10 different languages and observe consistent gains in the range 0.6%-5.2% by leveraging ... : Submitted to Interspeech 2022 ...
Keyword:
Audio and Speech Processing eess.AS
;
Computation and Language cs.CL
;
FOS Computer and information sciences
;
FOS Electrical engineering, electronic engineering, information engineering
;
Machine Learning cs.LG
;
Sound cs.SD
URL:
https://arxiv.org/abs/2204.02263
https://dx.doi.org/10.48550/arxiv.2204.02263
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2
ADIMA: Abuse Detection In Multilingual Audio ...
Gupta, Vikram
;
Sharon, Rini
;
Sawhney, Ramit
. - : arXiv, 2022
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