Enhancing stress speech classification through the fusion of emotional datasets utilizing MFCCs with CNN

• Main Authors: Zainal, Nur Aishah, Asnawi, Ani Liza
• Format: Proceeding Paper
• Language: English; English
• Published: IEEE 2024
• Subjects: TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices; TK7885 Computer engineering
• Online Access: http://irep.iium.edu.my/114504/7/114504_Enhancing%20Stress%20Speech%20Classification%20Through%20the%20Fusion%20of%20Emotional%20Datasets%20Utilizing%20MFCCs%20with%20CNN.pdf; http://irep.iium.edu.my/114504/1/Enhancing%20Stress%20Speech%20Classification%20Through%20the%20Fusion%20of%20Emotional%20Datasets%20Utilizing%20MFCCs%20with%20CNN.pdf; http://irep.iium.edu.my/114504/; https://ieeexplore.ieee.org/abstract/document/10652270
• Institution: Universiti Islam Antarabangsa Malaysia

Stress classification involves categorizing an individual's perceived stress state. One approach involves analyzing human speech due to its non-invasive nature, offering advantages over traditional methods requiring intrusive procedures. Presently, two main types of datasets are used in th...