TY - GEN
T1 - BS-GSA
T2 - 15th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2023
AU - Zhang, Yichi
AU - Yang, Xinyu
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Speech emotion recognition (SER) is an indispensable part of human intention understanding in human-computer interaction systems. In this paper, we propose a novel Blend-Sample empowered Global & Spectral Attentive (BS-GSA) paradigm for more robust global and spectral emotional feature learning. The Global & Spectral Attentive (GSA) model captures global and positional information with attentive model design, devotes to better learning emotional representation from long-term dependencies and spectral characteristics. Besides, we propose a blend-sample (BS) augmentation algorithm for equilibrated emotion samples and better learning of inconspicuous frame-level emotion clues. Experiments conducted on the IEMOCAP dataset demonstrate that the proposed paradigm outperforms existing methods, reaching state-of-the-art performance.
AB - Speech emotion recognition (SER) is an indispensable part of human intention understanding in human-computer interaction systems. In this paper, we propose a novel Blend-Sample empowered Global & Spectral Attentive (BS-GSA) paradigm for more robust global and spectral emotional feature learning. The Global & Spectral Attentive (GSA) model captures global and positional information with attentive model design, devotes to better learning emotional representation from long-term dependencies and spectral characteristics. Besides, we propose a blend-sample (BS) augmentation algorithm for equilibrated emotion samples and better learning of inconspicuous frame-level emotion clues. Experiments conducted on the IEMOCAP dataset demonstrate that the proposed paradigm outperforms existing methods, reaching state-of-the-art performance.
KW - attention mechanism
KW - convolutional neural network
KW - human-computer interaction
KW - speech emotion recognition
UR - https://www.scopus.com/pages/publications/85186758221
U2 - 10.1109/CyberC58899.2023.00034
DO - 10.1109/CyberC58899.2023.00034
M3 - 会议稿件
AN - SCOPUS:85186758221
T3 - Proceedings - 2023 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2023
SP - 155
EP - 158
BT - Proceedings - 2023 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 2 November 2023 through 4 November 2023
ER -