Robust blind approach for digital speech watermarking

2018 ◽  
Author(s):  
Ahmed Merrad ◽  
Ali Benziane ◽  
Slami Saadi ◽  
Ahmed Hafaifa
Keyword(s):  
Speech Watermarking ◽  
Digital Speech Watermarking

Speaker Frame Selection for Digital Speech Watermarking

2016 ◽  
Vol 39 (3) ◽  
pp. 197-201 ◽  
Author(s):  
Mohammad Ali Nematollahi ◽  
S. A. R. Al-Haddad ◽  
Shyamala Doraisamy ◽  
Hamurabi Gamboa-Rosales
Keyword(s):  
Frame Selection ◽  
Speech Watermarking ◽  
Digital Speech Watermarking ◽  
Selection For

scholarly journals A HIGH SPEED VLSI ARCHITECTURE FOR DIGITAL SPEECH WATERMARKING WITH COMPRESSION

2014 ◽  
pp. 264-269
Author(s):  
RAJA SREE. AVIRNENI ◽  
K. PADMA VASAVI
Keyword(s):  
Digital Watermarking ◽  
High Speed ◽  
Vlsi Architecture ◽  
Periodic Coefficient ◽  
Multimedia Data ◽  
Speech Compression ◽  
Speech Watermarking ◽  
Wide Range ◽  
Digital Speech Watermarking ◽  
Dsp Processors

The need to provide a copy right protection on digital watermarking to multimedia data like speech, image or video is rapidly increasing with an intensification in the application in these areas. Digital watermarking has received a lot of attention in the past few years. A hardware system based solely on DSP processors are fast but may require more area, cost or power if the target application requires a large amount of parallel processing. An FPGA co-processor can provide as many as 550 parallel multiply and accumulate operations on a single device, but FPGAs excel at processing large amounts of data in parallel, as they are not optimized as processors for tasks such as periodic coefficient updates, decision- making control tasks. Combination of both the FPGA and DSP processor delivers an attractive solution for a wide range of applications. A hardware implementation of digital speech watermarking combined with speech compression, encryption on heterogeneous platform is made in this paper. It is observed that the proposed architecture is able to attain high speed while utilizing optimal resources in terms of area.

scholarly journals An overview of digital speech watermarking

2013 ◽  
Vol 16 (4) ◽  
pp. 471-488 ◽  
Author(s):  
Mohammad Ali Nematollahi ◽  
S. A. R. Al-Haddad
Keyword(s):  
Speech Watermarking ◽  
Digital Speech Watermarking

scholarly journals Semi-fragile digital speech watermarking for online speaker recognition

2015 ◽  
Vol 2015 (1) ◽  
Author(s):  
Mohammad Ali Nematollahi ◽  
Mohammad Ali Akhaee ◽  
S. A. R. Al-Haddad ◽  
Hamurabi Gamboa-Rosales
Keyword(s):  
Speaker Recognition ◽  
Speech Watermarking ◽  
Digital Speech Watermarking

Digital Speech Watermarking Based on Linear Predictive Analysis and Singular Value Decomposition

2017 ◽  
Vol 87 (3) ◽  
pp. 433-446 ◽  
Author(s):  
Mohammad Ali Nematollahi ◽  
Chalee Vorakulpipat ◽  
Hamurabi Gamboa-Rosales ◽  
Francisco J. Martinez-Ruiz ◽  
Jose I. De la Rosa-Vargas
Keyword(s):  
Singular Value Decomposition ◽  
Singular Value ◽  
Predictive Analysis ◽  
Speech Watermarking ◽  
Digital Speech Watermarking ◽  
Value Decomposition ◽  
Linear Predictive Analysis

scholarly journals Robust Digital Speech Watermarking For Online Speaker Recognition

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Mohammad Ali Nematollahi ◽  
Hamurabi Gamboa-Rosales ◽  
Mohammad Ali Akhaee ◽  
S. A. R. Al-Haddad
Keyword(s):  
Speaker Recognition ◽  
Speaker Verification ◽  
Discrete Wavelet ◽  
Specific Information ◽  
Massachusetts Institute ◽  
Massachusetts Institute Of Technology ◽  
Discrete Wavelet Packet Transform ◽  
Speech Watermarking ◽  
Digital Speech Watermarking ◽  
Institute Of Technology

A robust and blind digital speech watermarking technique has been proposed for online speaker recognition systems based on Discrete Wavelet Packet Transform (DWPT) and multiplication to embed the watermark in the amplitudes of the wavelet’s subbands. In order to minimize the degradation effect of the watermark, these subbands are selected where less speaker-specific information was available (500 Hz–3500 Hz and 6000 Hz–7000 Hz). Experimental results on Texas Instruments Massachusetts Institute of Technology (TIMIT), Massachusetts Institute of Technology (MIT), and Mobile Biometry (MOBIO) show that the degradation for speaker verification and identification is 1.16% and 2.52%, respectively. Furthermore, the proposed watermark technique can provide enough robustness against different signal processing attacks.

Sign in / Sign up

Export Citation Format

Share Document