Bi-Modal Bi-Task Emotion Recognition Based on Transformer Architecture
In the field of emotion recognition, analyzing emotions from speech alone (single-modal speech emotion recognition) has several limitations, including limited data volume and low accuracy. Additionally, single-task models lack generalization and fail to fully utilize relevant information. To address...
Saved in:
| Main Authors: | Yu Song, Qi Zhou |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Applied Artificial Intelligence |
| Online Access: | https://www.tandfonline.com/doi/10.1080/08839514.2024.2356992 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The Relationship between Task Characteristics, BI Quality, and Task Compatibility: An Explorative Study
by: Rikke Gaardboe, et al.
Published: (2018-04-01) -
Intelligent quality control method for marine buoy data based on transformer encoder and BiLSTM
by: Miaomiao Song, et al.
Published: (2025-04-01) -
Dimensions of Fractals Generated by Bi-Lipschitz Maps
by: Qi-Rong Deng, et al.
Published: (2014-01-01) -
Construction of knowledge graph for gas polyethylene pipelines based on ALBERT-BiGRU-CRF
by: Zhilong Yu, et al.
Published: (2025-07-01) -
Cooling Load Forecasting Method for Central Air Conditioning Systems in Manufacturing Plants Based on iTransformer-BiLSTM
by: Xiaofeng Huang, et al.
Published: (2025-05-01)