M2ER: Multimodal Emotion Recognition Based on Multi-Party Dialogue Scenarios
Researchers have recently focused on multimodal emotion recognition, but issues persist in recognizing emotions in multi-party dialogue scenarios. Most studies have only used text and audio modality, ignoring the video modality. To address this, we propose M2ER, a <b>m</b>ultimodal <b...
Main Authors: | Bo Zhang, Xiya Yang, Ge Wang, Ying Wang, Rui Sun |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-10-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/13/20/11340 |
Similar Items
-
Survey of Deep Learning Based Multimodal Emotion Recognition
by: ZHAO Xiaoming, YANG Yijiao, ZHANG Shiqing
Published: (2022-07-01) -
Multimodal Emotion Recognition Fusion Analysis Adapting BERT With Heterogeneous Feature Unification
by: Sanghyun Lee, et al.
Published: (2021-01-01) -
Multimodal Attention Network for Continuous-Time Emotion Recognition Using Video and EEG Signals
by: Dong Yoon Choi, et al.
Published: (2020-01-01) -
MemoCMT: multimodal emotion recognition using cross-modal transformer-based feature fusion
by: Mustaqeem Khan, et al.
Published: (2025-02-01) -
Robust Multimodal Emotion Recognition from Conversation with Transformer-Based Crossmodality Fusion
by: Baijun Xie, et al.
Published: (2021-07-01)