A low-rank matching attention based cross-modal feature fusion method for conversational emotion recognition
Conversational emotion recognition (CER) is an important research topic in human-
computer interactions. Although recent advancements in transformer-based cross-modal …
computer interactions. Although recent advancements in transformer-based cross-modal …
Supervised prototypical contrastive learning for emotion recognition in conversation
Capturing emotions within a conversation plays an essential role in modern dialogue
systems. However, the weak correlation between emotions and semantics brings many …
systems. However, the weak correlation between emotions and semantics brings many …
Dualgats: Dual graph attention networks for emotion recognition in conversations
Capturing complex contextual dependencies plays a vital role in Emotion Recognition in
Conversations (ERC). Previous studies have predominantly focused on speaker-aware …
Conversations (ERC). Previous studies have predominantly focused on speaker-aware …
[HTML][HTML] A mental state Knowledge–aware and Contrastive Network for early stress and depression detection on social media
Stress and depression detection on social media aim at the analysis of stress and
identification of depression tendency from social media posts, which provide assistance for …
identification of depression tendency from social media posts, which provide assistance for …
Supervised adversarial contrastive learning for emotion recognition in conversations
Extracting generalized and robust representations is a major challenge in emotion
recognition in conversations (ERC). To address this, we propose a supervised adversarial …
recognition in conversations (ERC). To address this, we propose a supervised adversarial …
Cluster-level contrastive learning for emotion recognition in conversations
A key challenge for Emotion Recognition in Conversations (ERC) is to distinguish
semantically similar emotions. Some works utilise Supervised Contrastive Learning (SCL) …
semantically similar emotions. Some works utilise Supervised Contrastive Learning (SCL) …
A Facial Expression-Aware Multimodal Multi-task Learning Framework for Emotion Recognition in Multi-party Conversations
Abstract Multimodal Emotion Recognition in Multiparty Conversations (MERMC) has
recently attracted considerable attention. Due to the complexity of visual scenes in multi …
recently attracted considerable attention. Due to the complexity of visual scenes in multi …
[HTML][HTML] PHQ-aware depressive symptoms identification with similarity contrastive learning on social media
Depressive symptoms identification on social media aims to identify posts from social media
expressing symptoms of depression. This can be beneficial for developing mental health …
expressing symptoms of depression. This can be beneficial for developing mental health …
Two birds with one stone: Knowledge-embedded temporal convolutional transformer for depression detection and emotion recognition
W Zheng, L Yan, FY Wang - IEEE Transactions on Affective …, 2023 - ieeexplore.ieee.org
Depression is a critical problem in modern society that affects an estimated 350 million
people worldwide, causing feelings of sadness and a lack of interest and pleasure …
people worldwide, causing feelings of sadness and a lack of interest and pleasure …
EmotionIC: emotional inertia and contagion-driven dependency modeling for emotion recognition in conversation
Emotion recognition in conversation (ERC) has attracted growing attention in recent years
as a result of the advancement and implementation of human-computer interface …
as a result of the advancement and implementation of human-computer interface …