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Audio Watermarking for Security and Non-Security Applications /
2022
Details
Title
Audio Watermarking for Security and Non-Security Applications /
Author
Charfeddine, Maha, author.
Mezghani, Eya, author.
Masmoudi, Salma, author.
Amar, Chokri Ben, author.
Alhumyani, Hesham, author.
Mezghani, Eya, author.
Masmoudi, Salma, author.
Amar, Chokri Ben, author.
Alhumyani, Hesham, author.
Item Type
Article
Description
1 volume
Summary
The digitization of audiovisual data is significantly increasing. Thus, to guarantee the protection of the intellectual properties of this digital content, watermarking has appeared as a solution. Watermarking can be used in reality in several types of applications that target two different contexts: the first for security applications and the second for non-security ones. In this paper, we carry a big interest in studying these two types of applications. Moreover, we propose a first digital watermarking scheme for security copyright protection applications, where we have involved neural network architecture in the insertion and detection processes, and integrated some masking phenomena of the human psychoacoustic model with linear predictive coding spectral envelope estimation of the audio file. Experiments proved the efficiency of exploiting perceptual masking with spectral envelope consideration in terms of imperceptibility and robustness results. In addition, we suggest a second audio watermarking technique for non-security content characterization applications based on a deep learning classification architecture. In this scheme, the extracted watermark advises about the audio class: music or speech, speaker gender, and emotion. The reported results indicated that the suggested scheme achieved a higher performance at the classification level, as well as at the watermarking properties.
Note
ISSN: 2169-3536
This resource was extracted from the Directory of Open Access Journals (DOAJ)
This resource was extracted from the Directory of Open Access Journals (DOAJ)
Source of Description
Crossref
Series
IEEE Access ; Volume 10, pp. 12654-12677, 2022.
In
IEEE Access
Linked Resources
Online version
Published
United States: [IEEE], 2022
Language
English
Record Appears in
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