Dual-feature speech emotion recognition fusion algorithm based on wavelet scattering transform and MFCC
A fusion algorithm named permutation entropy weighted and bias adjustment rule fusion (PEW-BAR) was proposed to enhance the accuracy of speech emotion recognition by exploiting the emotional information in the spectral characteristics of speech signals. The algorithm was based on the integration of...
Saved in:
Main Authors: | YING Na, WU Shunpeng, YANG Meng, ZOU Yujian |
---|---|
Format: | Article |
Language: | zho |
Published: |
Beijing Xintong Media Co., Ltd
2024-05-01
|
Series: | Dianxin kexue |
Subjects: | |
Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2024088/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
WTASR: Wavelet Transformer for Automatic Speech Recognition of Indian Languages
by: Tripti Choudhary, et al.
Published: (2023-03-01) -
Continuous Speech-Based Fatigue Detection and Transition State Prediction for Air Traffic Controllers
by: Susmitha Vekkot, et al.
Published: (2025-01-01) -
AFT-SAM: Adaptive Fusion Transformer with a Sparse Attention Mechanism for Audio–Visual Speech Recognition
by: Na Che, et al.
Published: (2024-12-01) -
Plant Leaf Identification Using Feature Fusion of Wavelet Scattering Network and CNN With PCA Classifier
by: S. Gowthaman, et al.
Published: (2025-01-01) -
Classification of Speech Emotion State Based on Feature Map Fusion of TCN and Pretrained CNN Model From Korean Speech Emotion Data
by: A-Hyeon Jo, et al.
Published: (2025-01-01)