Speech Emotion Recognition by Combining a Unified First-Order Attention Network With Data Balance

Speech Emotion Recognition by Combining a Unified First-Order Attention Network With Data Balance

In the domain of speech emotion recognition (SER), generally there is an unbalanced data distribution of emotional samples in existing emotional datasets. Moreover, different fragment areas in an utterance contribute diversely to SER. To address these two issues, this paper proposes a new SER method...

Full description

Bibliographic Details
Main Authors: Gang Chen, Shiqing Zhang, Xin Tao, Xiaoming Zhao
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Speech emotion recognition
first-order attention
data balance
convolutional neural network
bi-directional long short-term memory
Online Access:https://ieeexplore.ieee.org/document/9261367/

Internet

https://ieeexplore.ieee.org/document/9261367/

Similar Items