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Found 2 papers, 1 papers with code
Context-Dependent Embedding Utterance Representations for Emotion Recognition in Conversations
The usual approach to model the conversational context has been to produce context-independent representations of each utterance and subsequently perform contextual modeling of these.
Ranked #1 on
Emotion Recognition in Conversation
on EmoWoz
(Macro F1 metric)
Towards a Sentiment-Aware Conversational Agent
In this paper, we propose an end-to-end sentiment-aware conversational agent based on two models: a reply sentiment prediction model, which leverages the context of the dialogue to predict an appropriate sentiment for the agent to express in its reply; and a text generation model, which is conditioned on the predicted sentiment and the context of the dialogue, to produce a reply that is both context and sentiment appropriate.
