RNN model for Emotion Recognition in Dialogue by incorporating the Attention on the Other’s State

Seunguook Lim, Jihie Kim

http://doi.org/10.5626/JOK.2021.48.7.802

Emotion recognition has increasingly received much attention in artificial intelligence, lately. In this paper, we present an RNN model that analyzes and identifies a speaker’s emotion appeared through utterances in conversation. There are two kinds of speaker considered context, self-dependency and inter-speaker dependency. In particular, we focus more on inter-speaker dependency by considering that the state context information of the relative speaker can affect the emotions of the current speaker. We propose a DialogueRNN based model that adds a new GRU Cell for catching inter-speaker dependency. Our model shows higher performance than the performances of DialogueRNN and its three variants on multiple emotion classification datasets.