Adaptive Graph Learning for Multimodal Conversational Emotion Detection
Multimodal Emotion Recognition in Conversations (ERC) aims to identify the emotions
conveyed by each utterance in a conversational video. Current efforts encounter challenges …
conveyed by each utterance in a conversational video. Current efforts encounter challenges …
A Multi-Level Alignment and Cross-Modal Unified Semantic Graph Refinement Network for Conversational Emotion Recognition
X Zhang, W Cui, B Hu, Y Li - IEEE Transactions on Affective …, 2024 - ieeexplore.ieee.org
Emotion recognition in conversation (ERC) based on multiple modalities has attracted
enormous attention. However, most research simply concatenated multimodal …
enormous attention. However, most research simply concatenated multimodal …
A Training-Free Debiasing Framework with Counterfactual Reasoning for Conversational Emotion Detection
Unintended dataset biases typically exist in existing Emotion Recognition in Conversations
(ERC) datasets, including label bias, where models favor the majority class due to …
(ERC) datasets, including label bias, where models favor the majority class due to …
[PDF][PDF] Multilingual emotion recognition: Discovering the variations of lexical semantics between languages
The task of multilingual emotion recognition holds significant importance in cross-cultural
communication and data mining. While prior research has concentrated on enhancing …
communication and data mining. While prior research has concentrated on enhancing …
Learning More from Mixed Emotions: A Label Refinement Method for Emotion Recognition in Conversations
One-hot labels are commonly employed as ground truth in Emotion Recognition in
Conversations (ERC). However, this approach may not fully encompass all the emotions …
Conversations (ERC). However, this approach may not fully encompass all the emotions …
A Persona-Infused Cross-Task Graph Network for Multimodal Emotion Recognition with Emotion Shift Detection in Conversations
Recent research in Multimodal Emotion Recognition in Conversations (MERC) focuses on
multimodal fusion and modeling speaker-sensitive context. In addition to contextual …
multimodal fusion and modeling speaker-sensitive context. In addition to contextual …
Do topic and causal consistency affect emotion cognition? a graph interactive network for conversational emotion detection
K Gal - 2023 - ebooks.iospress.nl
Emotion recognition in conversations (ERC) typically requires modeling both intra-and inter-
speaker context dependencies. However, when modeling inter-speaker dependencies, it …
speaker context dependencies. However, when modeling inter-speaker dependencies, it …
Dialogue emotion model based on local–global context encoder and commonsense knowledge fusion attention
Abstract Emotion Recognition in Conversation (ERC) is a task aimed at predicting the
emotions conveyed by an utterance in a dialogue. It is common in ERC research to integrate …
emotions conveyed by an utterance in a dialogue. It is common in ERC research to integrate …
HITSZ-HLT at WASSA-2024 Shared Task 2: Language-agnostic Multi-task Learning for Explainability of Cross-lingual Emotion Detection
This paper describes the system developed by the HITSZ-HLT team for WASSA-2024
Shared Task 2, which addresses two closely linked sub-tasks: Cross-lingual Emotion …
Shared Task 2, which addresses two closely linked sub-tasks: Cross-lingual Emotion …
Attention mechanism optimization for sub-symbolic-based and neural-symbolic-based natural language processing
J Ni - 2023 - dr.ntu.edu.sg
The capability for machines to transduce, understand, and reason with natural language
lives at the heart of Artificial Intelligence not only because natural language is one of the …
lives at the heart of Artificial Intelligence not only because natural language is one of the …