Speech Watermarking Technique Based on Singular Spectrum Analysis and Automatic Parameter Estimation using Differential Evolution for Tampering Detection

2018 ◽  
Author(s):  
Kasorn Galajit ◽  
Jessada Karnjana ◽  
Masashi Unoki ◽  
Mongkonchai Intarauksorn ◽  
Pakinee Aimmanee
Keyword(s):  
Parameter Estimation ◽  
Differential Evolution ◽  
Spectrum Analysis ◽  
Singular Spectrum Analysis ◽  
Tampering Detection ◽  
Speech Watermarking ◽  
Singular Spectrum

scholarly journals Semi-fragile speech watermarking based on singular-spectrum analysis with CNN-based parameter estimation for tampering detection

2019 ◽  
Vol 8 ◽  
Author(s):  
Kasorn Galajit ◽  
Jessada Karnjana ◽  
Masashi Unoki ◽  
Pakinee Aimmanee
Keyword(s):  
Parameter Estimation ◽  
Spectrum Analysis ◽  
Singular Spectrum Analysis ◽  
Computational Time ◽  
Speech Signals ◽  
Hidden Information ◽  
Speech Watermarking ◽  
Singular Spectrum ◽  
Watermarking Scheme ◽  
Host Signal

AbstractA semi-fragile watermarking scheme is proposed in this paper for detecting tampering in speech signals. The scheme can effectively identify whether or not original signals have been tampered with by embedding hidden information into them. It is based on singular-spectrum analysis, where watermark bits are embedded into speech signals by modifying a part of the singular spectrum of a host signal. Convolutional neural network (CNN)-based parameter estimation is deployed to quickly and properly select the part of the singular spectrum to be modified so that it meets inaudibility and robustness requirements. Evaluation results show that CNN-based parameter estimation reduces the computational time of the scheme and also makes the scheme blind, i.e. we require only a watermarked signal in order to extract a hidden watermark. In addition, a semi-fragility property, which allows us to detect tampering in speech signals, is achieved. Moreover, due to the time efficiency of the CNN-based parameter estimation, the proposed scheme can be practically used in real-time applications.

Filtering and parameter estimation of surface-NMR data using singular spectrum analysis

2016 ◽  
Vol 130 ◽  
pp. 118-130 ◽  
Author(s):  
Reza Ghanati ◽  
Mohammad Kazem Hafizi ◽  
Rahim Mahmoudvand ◽  
Mahdi Fallahsafari
Keyword(s):  
Parameter Estimation ◽  
Spectrum Analysis ◽  
Singular Spectrum Analysis ◽  
Singular Spectrum ◽  
Nmr Data
Sign in / Sign up

Export Citation Format

Share Document