awesome-emotion-recognition-in-conversations
github.com/declare-lab/awesome-emotion-recognition-in-conversations ↗A comprehensive reading list for Emotion Recognition in Conversations
279
GitHub Stars
95
Curated Resources
7
Categories
2 hours ago
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OverviewsData ResourcesERCContextual Sentiment AnalysisContexutal Sarcasm AnalysisOthersWorkshops and Shared Tasks
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ERC
- Adapted Dynamic Memory Network for Emotion Recognition in Conversation
- Adapted Dynamic Memory Network for Emotion Recognition in Conversation
- A Dialogical Emotion Decoder for Speech Motion Recognition in Spoken Dialog
- Analysis of Utterance Combinations for Emotion Recognition in Conversation
- An Effective Deep Learning Approach for Dialogue Emotion Recognition in Car-Hailing Platform
- An interaction-aware attention network for speech emotion recognition in spoken dialogs
Contexutal Sarcasm Analysis
- A Novel Hierarchical BERT Architecture for Sarcasm Detection
- Applying Transformers and Aspect-based Sentiment Analysis approaches on Sarcasm Detection
- C-Net: Contextual Network for Sarcasm Detection
- Context-Aware Sarcasm Detection Using BERT
- Detecting Sarcasm in Conversation Context Using Transformer-Based Models
- MUStARD: Towards Multimodal Sarcasm Detection (An Obviously Perfect Paper)
Contextual Sentiment Analysis
- A Quantum-like Multimodal Network Framework for Modeling Interaction Dynamics in Multiparty Conversational Sentiment Analysis
- DCR-Net: A Deep Co-Interactive Relation Network for Joint Dialog Act Recognition and Sentiment Classification
- Quantum-Inspired DMATT-BiGRU for Conversational Sentiment Analysis
- Quantum-Inspired Interactive Networks for Conversational Sentiment Analysis
- Sentiment Forecasting in Dialog
Overviews
Data Resources
- DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
- Emotional Dialogue Acts
- Emotionlines: An emotion corpus of multi-party conversations
- IEMOCAP: Interactive emotional dyadic motion capture database
- K-EmoCon, a multimodal sensor dataset for continuous emotion recognition in naturalistic conversations
- MEISD: A Multimodal Multi-Label Emotion, Intensity and Sentiment Dialogue Dataset for Emotion Recognition and Sentiment Analysis in Conversations
Workshops and Shared Tasks
Showing a sample of 95 resources. View the full list on GitHub →