Emotions are an inherent part of human interactions, and consequently, it is imperative to
develop AI systems that understand and recognize human emotions. During a conversation …

Multimodal emotion recognition aims to recognize emotions for each utterance of multiple
modalities, which has received increasing attention for its application in human-machine …

Understanding the emotional polarity of multimodal content with metaphorical
characteristics, such as memes, poses a significant challenge in Multimodal Emotion …

Purpose: Manifestations of emotion in social conversational interactions stand at a focal
point in the rapidly growing affective computing area, with applications in healthcare …

In the rapidly expanding domain of multimodal data, the field of emotion analysis has
advanced through the sophisticated integration of diverse informational modalities. This …

Designed for tracking user goals in dialogues, a dialogue state tracker is an essential
component in a dialogue system. However, the research of dialogue state tracking has …

In recent years, sentiment analysis in conversation has garnered increasing attention due to
its widespread applications in areas such as social media analytics, sentiment mining, and …

Emotion Recognition in Conversations (ERC) is an important aspect of affective computing
with practical applications in healthcare, education, chatbots, and social media platforms …

Multimodal Emotion Recognition in Conversations (MERC) has garnered significant
attention due to its potential applicability in various real-world scenarios. Key challenges in …

The recent developments in technologies bring not only increasing amount of information
but also multiple information sources for Graph Representation Learning. With the success …