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Elvis Saravia

Editor at dair.ai

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This is an oral presentation I delivered in Brussels, Belgium at the EMNLP 2018 conference for the paper “CARER: Contextualized Affect Representations for Emotion Recognition”

Abstract


Emotions are expressed in nuanced ways, which varies by collective or individual experiences, knowledge, and beliefs. Therefore, to understand emotion, as conveyed through text, a robust mechanism capable of capturing and modeling different linguistic nuances and phenomena is needed. We propose a semi-supervised, graph-based algorithm to produce rich structural descriptors which serve as the building blocks for constructing contextualized affect representations from text. The pattern-based representations are further enriched with word embeddings and evaluated through several emotion recognition tasks. Our experimental results demonstrate that the proposed method outperforms state-of-the-art techniques on emotion recognition tasks.


Link to Video


Link to Paper