Spoofing speech attack detection based on EfficientNet

Zhuoyi Su

doi:10.1117/12.3031059

19 July 2024 Spoofing speech attack detection based on EfficientNet

Zhuoyi Su

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131812Y (2024) https://doi.org/10.1117/12.3031059
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

With the rapid development and wide application of speech technology, the use of spoofing speech has become a serious problem. Spoofing speech can be maliciously used to fake information, identity fraud and other activities, which brings serious risks to society. Therefore, effective spoofing speech attack detection methods become essential. In this paper, we propose a spoofing speech attack detection method based on EfficientNet. The feature maps obtained by speech conversion are input into the designed EfficientNet, and a classifier is used to determine the spoofing speech. The experimental results show that the EficientNets-B5 detection model is more than 90% accurate in dealing with various types of spoofing attacks, and the equal error rate is the lowest of 5.82%.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhuoyi Su "Spoofing speech attack detection based on EfficientNet", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131812Y (19 July 2024); https://doi.org/10.1117/12.3031059

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