Hybrid Transformer Architectures With Diverse Audio Features for Deepfake Speech Classification

Hybrid Transformer Architectures With Diverse Audio Features for Deepfake Speech Classification

The rise of synthetic speech technologies has triggered growing concerns about the increasing difficulty in distinguishing between real and fake voices. In this context, we propose novel hybrid transformer-based models together with different audio feature analysis techniques and achieved the state-...

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Bibliographic Details
Main Authors: Khalid Zaman, Islam J. A. M. Samiul, Melike Sah, Cem Direkoglu, Shogo Okada, Masashi Unoki
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Transformer
CNN-Transformer
ResNet-Transformer
VGG16-Transformer
Transformer-SVM
fusion models
Online Access:https://ieeexplore.ieee.org/document/10714458/

Internet

https://ieeexplore.ieee.org/document/10714458/

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