Emotion Recognition in Conversation
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Benchmarks
MELD
IEMOCAP
EmoryNLP
DailyDialog
CPED
EC
IEMOCAP-4
CMU-MOSEI-Sentiment
EmoWoz
SEMAINE
CMU-MOSEI-Sentiment-3
CMU-MOSI
EmoWOZ
EmotionPush
KD-EmoR
MELD-Sentiment
Most implemented
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Convolutional Neural Networks for Sentence Classification
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
Bag of Tricks for Efficient Text Classification
DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion Recognition
Papers
DiaRelay: Relaying Dialogue Context with a Constant-Size Memory for Emotion Recognition in Conversation
Emotion Recognition in Conversation (ERC) requires models to identify subtle emotional cues that are often distributed across distant dialogue turns. Existing methods typically incorporate dialogue history through a fixe…
Emotion Recognition in ConversationS2Dialog: Multimodal Dialogue Retrieval with Semantic and Acoustic-Style Modeling
Multimodal dialogue retrieval aims to retrieve dialogues from multimodal dialogue banks that are similar to a target dialogue in terms of both textual semantics and acoustic conversational styles. Such dialogue-level ret…
Emotion Recognition in ConversationContrastive LearningSpeech SynthesisAtmosERC: Modeling Dialogue-Level Affective Atmosphere for Emotion Recognition in Conversation
Emotion Recognition in Conversation (ERC) aims to predict utterance-level emotions in dialogues and has largely advanced through context-centric modeling. However, global context is a heterogeneous signal, and not all co…
Emotion Recognition in ConversationEmotion Recognition in Sign Language Conversation
Emotion Recognition in Conversation is a core component of affective computing, while current resources of sign language emotion datasets primarily focus on isolated sentences and lack conversational context. Models trai…
Emotion Recognition in ConversationVISAFF: Speaker-Centered Visual Affective Feature Learning for Emotion Recognition in Conversation
Emotion Recognition in Conversation (ERC) is essential for effective human-machine interaction, aiming to identify speakers' emotional states in multi-turn dialogues. Early text-based methods struggle with complex scenar…
Emotion Recognition in ConversationComputational EfficiencySELF-EMO: Emotional Self-Evolution from Recognition to Consistent Expression
Emotion Recognition in Conversation (ERC) has become a fundamental capability for large language models (LLMs) in human-centric interaction. Beyond accurate recognition, coherent emotional expression is also crucial, yet…
Emotion Recognition in ConversationReinforcement Learning