N. Vryzas, A. Katsaounidou, R. Kotsakis, C. A. Dimoulas, and G. Kalliris, “Audio-Driven Multimedia Content Authentication as a Service,” in Proc. AES Convention 146, Mar. 2019, Paper 10148. [Online]. Available: https://aes.org/publications/elibrary-page/?id=20281
Vryzas N, Katsaounidou A, Kotsakis R, Dimoulas CA, Kalliris G. Audio-Driven Multimedia Content Authentication as a Service. In: AES Convention 146. Audio Engineering Society; 2019. Paper 10148. Available from: https://aes.org/publications/elibrary-page/?id=20281
@inproceedings{Vryzas2019_20281,
author = {Vryzas, Nikolaos and Katsaounidou, Anastasia and Kotsakis, Rigas and Dimoulas, Charalampos A. and Kalliris, George},
title = {{Audio-Driven Multimedia Content Authentication as a Service}},
booktitle = {AES Convention 146},
note = {Paper 10148},
year = {2019},
month = mar,
publisher = {Audio Engineering Society},
url = {https://aes.org/publications/elibrary-page/?id=20281}
}
TY - CPAPER
TI - Audio-Driven Multimedia Content Authentication as a Service
AU - Vryzas, Nikolaos
AU - Katsaounidou, Anastasia
AU - Kotsakis, Rigas
AU - Dimoulas, Charalampos A.
AU - Kalliris, George
T2 - AES Convention 146
M1 - Paper 10148
PY - 2019
DA - 2019/03/06
UR - https://aes.org/publications/elibrary-page/?id=20281
PB - Audio Engineering Society
LA - en
AB - In the current paper we present a framework for providing supervisory tools for multimedia Content Authentication As A Service (CAAAS). A double compression method for discontinuity detection in audio signals is implemented and integrated in the provided web service. The user can upload audio/video content or provide links and thereafter, a feature vector is extracted from the audio modality of the selected content for the investigation of discontinuities of the signal via the proposed algorithms. Several visualizations are returned to the user, indicating possible points of forgery in the audio/visual file. Moreover, an audio tampering detection methodology by unsupervised clustering of short-window non-vocal segments, in order to identify differentiations of the acoustic environment of speech signals is presented and evaluated.
ER -