SOTAVerified

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 125 of 141 papers

TitleStatusHype
BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingCode3
Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language ModelsCode3
CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AICode2
UniMSE: Towards Unified Multimodal Sentiment Analysis and Emotion RecognitionCode2
Structure-Aware Transformer for Graph Representation LearningCode2
Recent Trends of Multimodal Affective Computing: A Survey from NLP PerspectiveCode2
COSMIC: COmmonSense knowledge for eMotion Identification in ConversationsCode2
DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion RecognitionCode1
DialogueRNN: An Attentive RNN for Emotion Detection in ConversationsCode1
Directed Acyclic Graph Network for Conversational Emotion RecognitionCode1
Beyond Silent Letters: Amplifying LLMs in Emotion Recognition with Vocal NuancesCode1
A Facial Expression-Aware Multimodal Multi-task Learning Framework for Emotion Recognition in Multi-party ConversationsCode1
Bag of Tricks for Efficient Text ClassificationCode1
How to Enhance Causal Discrimination of Utterances: A Case on Affective ReasoningCode1
Curriculum Learning Meets Directed Acyclic Graph for Multimodal Emotion RecognitionCode1
CFN-ESA: A Cross-Modal Fusion Network with Emotion-Shift Awareness for Dialogue Emotion RecognitionCode1
DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in ConversationsCode1
BiosERC: Integrating Biography Speakers Supported by LLMs for ERC TasksCode1
Tracing Intricate Cues in Dialogue: Joint Graph Structure and Sentiment Dynamics for Multimodal Emotion RecognitionCode1
Convolutional Neural Networks for Sentence ClassificationCode1
Contextual Information and Commonsense Based Prompt for Emotion Recognition in ConversationCode1
COGMEN: COntextualized GNN based Multimodal Emotion recognitioNCode1
A Transformer-Based Model With Self-Distillation for Multimodal Emotion Recognition in ConversationsCode1
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in ConversationCode1
A Hierarchical Transformer with Speaker Modeling for Emotion Recognition in ConversationCode1
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