Semi-supervised multi-modal emotion recognition with cross-modal distribution matching

J Liang, R Li, Q Jin - Proceedings of the 28th ACM international …, 2020 - dl.acm.org
Automatic emotion recognition is an active research topic with wide range of applications.
Due to the high manual annotation cost and inevitable label ambiguity, the development of …

Position bias mitigation: A knowledge-aware graph model for emotion cause extraction

H Yan, L Gui, G Pergola, Y He - arXiv preprint arXiv:2106.03518, 2021 - arxiv.org
The Emotion Cause Extraction (ECE)} task aims to identify clauses which contain emotion-
evoking information for a particular emotion expressed in text. We observe that a widely …

Building a large scale dataset for image emotion recognition: The fine print and the benchmark

Q You, J Luo, H Jin, J Yang - Proceedings of the AAAI conference on …, 2016 - ojs.aaai.org
Psychological research results have confirmed that people can have different emotional
reactions to different visual stimuli. Several papers have been published on the problem of …

Context-and sentiment-aware networks for emotion recognition in conversation

G Tu, J Wen, C Liu, D Jiang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Emotion recognition in conversation (ERC) has promising potential in many fields, such as
recommendation systems, man–machine interaction, and medical care. In contrast to other …

Speaker-invariant adversarial domain adaptation for emotion recognition

Y Yin, B Huang, Y Wu, M Soleymani - Proceedings of the 2020 …, 2020 - dl.acm.org
Automatic emotion recognition methods are sensitive to the variations across different
datasets and their performance drops when evaluated across corpora. We can apply …

Joint multi-level attentional model for emotion detection and emotion-cause pair extraction

H Tang, D Ji, Q Zhou - Neurocomputing, 2020 - Elsevier
Emotion detection (ED) and emotion-cause pair extraction (ECPE) have drawn extensive
research interests due to their wide applications in real-world scenarios. However, existing …

From independent prediction to reordered prediction: Integrating relative position and global label information to emotion cause identification

Z Ding, H He, M Zhang, R Xia - Proceedings of the AAAI Conference on …, 2019 - ojs.aaai.org
Emotion cause identification aims at identifying the potential causes that lead to a certain
emotion expression in text. Several techniques including rule based methods and traditional …

Two-stream aural-visual affect analysis in the wild

F Kuhnke, L Rumberg… - 2020 15th IEEE …, 2020 - ieeexplore.ieee.org
Human affect recognition is an essential part of natural human-computer interaction.
However, current methods are still in their infancy, especially for in-the-wild data. In this …

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 …

Multimodal emotion recognition with high-level speech and text features

MR Makiuchi, K Uto, K Shinoda - 2021 IEEE automatic speech …, 2021 - ieeexplore.ieee.org
Automatic emotion recognition is one of the central concerns of the Human-Computer
Interaction field as it can bridge the gap between humans and machines. Current works train …