Text classification in natural language processing (NLP) is evolving rapidly, particularly with
the surge in transformer-based models, including large language models (LLM). This paper …

Multi-modal conversation emotion recognition (MCER) aims to recognize and track the
speaker's emotional state using text, speech, and visual information in the conversation …

It has been a hot research topic to enable machines to understand human emotions in
multimodal contexts under dialogue scenarios, which is tasked with multimodal emotion …

Emotion recognition in conversations (ERC), the task of recognizing the emotion of each
utterance in a conversation, is crucial for building empathetic machines. Existing studies …

Abstract Emotion Recognition in Conversations (ERC) is an increasingly popular task in the
Natural Language Processing community, which seeks to achieve accurate emotion …

Abstract Multimodal Emotion Recognition in Multiparty Conversations (MERMC) has
recently attracted considerable attention. Due to the complexity of visual scenes in multi …

Multimodal intent recognition (MIR) aims to perceive the human intent polarity via language
visual and acoustic modalities. The inherent intent ambiguity makes it challenging to …

Understanding social interactions involving both verbal and non-verbal cues is essential for
effectively interpreting social situations. However most prior works on multimodal social cues …

Recently, speech-text pre-training methods have shown remarkable success in many
speech and natural language processing tasks. However, most previous pre-trained models …

Multimodal emotion recognition in conversation (ERC) has garnered growing attention from
research communities in various fields. In this paper, we propose a Cross-modal Fusion …