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[R] Emotion Recognition in Conversations with Graph Convolutional Neural Networks

Abstract: Emotion recognition in conversation (ERC) has received much attention, lately, from researchers due to its potential widespread applications in diverse areas, such as health-care, education, and human resources. In this paper, we present Dialogue Graph Convolutional Network (DialogueGCN), a graph neural network based approach to ERC. We leverage self and inter-speaker dependency of the interlocutors to model conversational context for emotion recognition. Through the graph network, DialogueGCN addresses context propagation issues present in the current RNN-based methods. We empirically show that this method alleviates such issues, while outperforming the current state of the art on a number of benchmark emotion classification datasets.

Paper: https://arxiv.org/abs/1908.11540 (EMNLP 2019)

Blog Post: https://towardsdatascience.com/emotion-recognition-using-graph-convolutional-networks-9f22f04b244e

I am the primary author of the paper. Feel free to ask questions.

submitted by /u/bideex
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.