TY - GEN
T1 - An Improved System for Partially Fake Audio Detection Using Pre-trained Model
AU - Zhang, Jianqian
AU - Liu, Hanyue
AU - Deng, Mengyuan
AU - Wang, Jing
AU - Sun, Yi
AU - Xu, Liang
AU - Li, Jiahao
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - The technology of speech synthesis and conversion has made good progress with the development of deep learning. However, such technology can also do harm to information security and may be applied for illegal uses. Therefore, researchers have conducted a lot of research on the task of speech deep forgery detection recently. Corresponding to this, the Audio Deep Synthesis Detection Challenge 2023 (ADD 2023) is held. In this paper, we propose a fake audio detecting system using a pre-trained model, focusing on partially fake audio detection tasks. We have presented our models to the ADD 2023 challenge. In the final competition, our system got a score of 0.4855 in the manipulation region location track.
AB - The technology of speech synthesis and conversion has made good progress with the development of deep learning. However, such technology can also do harm to information security and may be applied for illegal uses. Therefore, researchers have conducted a lot of research on the task of speech deep forgery detection recently. Corresponding to this, the Audio Deep Synthesis Detection Challenge 2023 (ADD 2023) is held. In this paper, we propose a fake audio detecting system using a pre-trained model, focusing on partially fake audio detection tasks. We have presented our models to the ADD 2023 challenge. In the final competition, our system got a score of 0.4855 in the manipulation region location track.
KW - audio deepfake detection
KW - deep-learning
KW - fake region location
KW - manipulation
UR - http://www.scopus.com/inward/record.url?scp=85186675762&partnerID=8YFLogxK
U2 - 10.1007/978-981-97-0601-3_30
DO - 10.1007/978-981-97-0601-3_30
M3 - Conference contribution
AN - SCOPUS:85186675762
SN - 9789819706006
T3 - Communications in Computer and Information Science
SP - 346
EP - 353
BT - Man-Machine Speech Communication - 18th National Conference, NCMMSC 2023, Proceedings
A2 - Jia, Jia
A2 - Ling, Zhenhua
A2 - Chen, Xie
A2 - Li, Ya
A2 - Zhang, Zixing
PB - Springer Science and Business Media Deutschland GmbH
T2 - 18th National Conference on Man-Machine Speech Communication, NCMMSC 2023
Y2 - 8 December 2023 through 11 December 2023
ER -