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Emotion Recognition in Conversation

Given the transcript of a conversation along with speaker information of each constituent utterance, the ERC task aims to identify the emotion of each utterance from several pre-defined emotions. Formally, given the input sequence of N number of utterances [(u1, p1), (u2, p2), . . . , (uN , pN )], where each utterance ui = [ui,1, ui,2, . . . , ui,T ] consists of T words ui,j and spoken by party pi, the task is to predict the emotion label ei of each utterance ui. .

Papers

Showing 6170 of 141 papers

TitleStatusHype
Context-Dependent Sentiment Analysis in User-Generated VideosCode0
EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue SystemsCode0
MONAH: Multi-Modal Narratives for Humans to analyze conversationsCode0
Dynamic Parameter Memory: Temporary LoRA-Enhanced LLM for Long-Sequence Emotion Recognition in ConversationCode0
Mimicking the Thinking Process for Emotion Recognition in Conversation with Prompts and ParaphrasingCode0
Recurrent Convolutional Neural Networks for Text ClassificationCode0
Accumulating Word Representations in Multi-level Context Integration for ERC TaskCode0
Knowledge-Enriched Transformer for Emotion Detection in Textual ConversationsCode0
ANA at SemEval-2019 Task 3: Contextual Emotion detection in Conversations through hierarchical LSTMs and BERTCode0
Deep Emotion Recognition in Textual Conversations: A SurveyCode0
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