An Intelligent System for Audio Splicing Forgery Detection Using MFCC
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-0562-7_29
Reference19 articles.
1. Yang R, Qu Z, Huang J (2008) Detecting digital audio forgeries by checking frame offsets. In: MM and Sec’08: Proceedings of the 10th ACM workshop on multimedia and security, pp 21–26
2. HCuccovillo L, Mann S, Tagliasacchi M, Aichroth P (2013) Audio tampering detection via microphone classification. In: 2013 IEEE international workshop on multimedia signal processing, MMSP 2013, vol 1, no 1, pp 177–182
3. Pan X, Zhang X, Lyu S (2012) Detecting splicing in digital audios using local noise level estimation. In: 2012 IEEE international conference on acoustics, speech and signal processing (ICASSP), pp 1841–1844
4. Lalitha NV, Srinivasa Rao C, JayaSree PVY (2019) Localization of copy-move forgery in speech signals through watermarking using DCT-QIM. Int J Electron Telecommun 65(3):527–532
5. Zhao H, Chen Y, Wang R, Malik H (2017) Audio splicing detection and localization using environmental signature. Multimed Tools Appl 76(12):13897–13927
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