Papers by Slim Essid

3 papers
Opinions in Interactions : New Annotations of the SEMAINE Database (2022.lrec-1)

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Challenge: a new method for the detection of opinions in interactions is proposed . a dataset of dyadic interactions is annotated continuously in two affective dimensions related to the emotions .
Approach: They propose to annotate opinions over a multimodal corpus of dyadic interactions . they use a d-acting algorithm to annnotate the opinions of a speaker .
Outcome: The proposed method allows to obtain a precise annotation regarding the opinion of a speaker.
From the Token to the Review: A Hierarchical Multimodal approach to Opinion Mining (D19-1)

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Challenge: Existing work on fine grained opinion annotations rely only on coarsely labeled opinions.
Approach: They propose to use hierarchical structure of opinions to build a fine and coarse grained opinion model that exploits different views of the opinion expression.
Outcome: The proposed model outperforms existing models on a recently released multimodal fine grained annotated corpus on IMDB and social networks.
iKnow-audio: Integrating Knowledge Graphs with Audio-Language Models (2025.emnlp-main)

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Challenge: Contrastive language-audio pretraining models learn by aligning audio and text in a shared embedding space.
Approach: They propose a framework that integrates knowledge graphs with audio-language models to provide robust semantic grounding.
Outcome: iKnow-audio improves disambiguation of acoustically similar sounds and reduces prompt engineering.

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