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Secure Transmission of Password Using Speech Watermarking

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TLDR
A blind speech watermarking algorithm that embeds the watermark signal data in the musical (sequence) host signal by using frequency masking is used and a different logarithmic approach is proposed.
Abstract
Internet is one of the most valuable resources for information communication and retrievals. Most multimedia signals today are in digital formats. The digital data can be duplicated and edited with great ease which has led to a need for data integrity and protection of digital data. The security requirements such as integrity or data authentication can be met by implementing security measures using digital watermarking techniques. In this paper a blind speech watermarking algorithm that embeds the watermark signal data in the musical (sequence) host signal by using frequency masking is used. A different logarithmic approach is proposed. In this regard a logarithmic function is first applied to watermark data. Then the transformed signal is embedded to the converted version of host signal which is obtained by applying Fast Fourier transform method. Finally using inverse Fast Fourier Transform and antilogarithmic function watermark signal is retrieved.

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Citations
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Journal ArticleDOI

Hybrid domain watermarking technique for copyright protection of images using speech watermarks

TL;DR: A watermarking technique based on various signal processing transforms is proposed and implemented for the security of image using human speech signal and performs better than the existing water marking techniques available in the literature.
Journal ArticleDOI

Watermarking Scheme with CS Encryption for Security and Piracy of Digital Audio Signals

TL;DR: The experimental results show that the proposed Proposedscheme for Curvelet Transform performs better than expected and is employed for both audio and speech watermarking.
Book ChapterDOI

Speech Watermarking Technique Using the Finite Ridgelet Transform, Discrete Wavelet Transform, and Singular Value Decomposition

TL;DR: A new watermarking technique is composed of the finite ridgelet transform, discrete wavelet transform (DWT), and singular value decomposition (SVD) and the security of the watermark information is provided using the Arnold scrambling technique.
Posted Content

Security issues in speech watermarking for information transmission

Rupa Patel, +1 more
- 25 Apr 2013 - 
TL;DR: Speech signal is normalized to hide the identity of the speaker who is sending the information and speech watermarking technique is applied on this normalized signal that contains the message (password) so that what information is transmitted should not be unauthorizedly revealed.
Proceedings ArticleDOI

Digital watermarking and tamper detection in speech signal using blind detection

TL;DR: An audio watermarking algorithm has been proposed which can be efficiently used for tamper detection and is also robust against reasonable attacks and makes tamper identification easier and gives framewise security.
References
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Book

Digital Watermarking and Steganography

TL;DR: This new edition now contains essential information on steganalysis and steganography, and digital watermark embedding is given a complete update with new processes and applications.
Journal ArticleDOI

Fast fourier transforms: a tutorial review and a state of the art

TL;DR: Note: V. Madisetti, D. B. Williams, Eds.

Fast Fourier transforms: a tutorial review and a state of the art

TL;DR: MadMadisetti, D. B. Williams, Eds. as discussed by the authors, LCAV-2005-009 Record created on 2005-06-27, modified on 2017-05-12

Algorithms for audio watermarking and steganography

TL;DR: The main results of this study are the development of novel audio watermarking algorithms, with the state-of-the-art performance and an acceptable increase in computational complexity.
Proceedings ArticleDOI

Performance of noise excitation for unvoiced speech

TL;DR: This paper addresses the question what perceptual quality can be achieved for unvoiced speech by a linear model with white noise excitation and demonstrates that this linear model results in unvoicing speech of high perceptual quality.
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