Speaker identification security improvement by means of speech watermarking

Journal of King Saud University - Computer and Information Scie

Zarafshan

2015

This paper presents a new blind digital speech watermarking technique based on Eigenvalue quantization in Discrete Wavelet Transform. Initially, each frame of the digital speech was transformed into the wavelet domain by applying Discrete Wavelet Transform. Then, the Eigenvalue of Approximation Coefficients was computed by using Singular Value Decomposition. Finally, the watermark bits were embedded by quantization of the Eigen-value. The experimental results show that this watermarking technique is robust against different attacks such as filtering, additive noise, resampling, and cropping. Applying new robust transforms, adaptive quantization steps and synchronization techniques can be the future trends in this field. ª 2014 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Section: Introductionmentioning

confidence: 99%

Blind digital speech watermarking based on Eigen-value quantization in DWT

Journal of King Saud University - Computer and Information Scie

Zarafshan

2015

“…However, the systems can be protected and secured against these attacks by time stamps and watermarking. Recently, speech watermarking has been used to secure communication channels for speaker verification and identification against both intentional and unintentional attacks [3][4][5][6]. For this purpose, the watermark is embedded to verify both the authenticity of the transmitter (i.e., using sensor and feature extractors) and the integrity of the entire authentication mechanism.…”

Section: Introductionmentioning

confidence: 99%

“…However, these techniques can seriously degrade speaker recognition performance. Also, watermarking and speaker recognition systems have opposing goals whenever the signal-to-watermark ratio (SWR) is reduced and the robustness of the watermark is increased, and the speaker identification and verification performance can be reduced [3][4][5]10]. Some researchers therefore apply semi-fragile watermarking methods to reduce the effects on recognition performance [11].…”

Section: Introductionmentioning

confidence: 99%

Semi-fragile digital speech watermarking for online speaker recognition

Akhaee

J AUDIO SPEECH MUSIC PROC.

et al. 2015

In this paper, a semi-fragile and blind digital speech watermarking technique for online speaker recognition systems based on the discrete wavelet packet transform (DWPT) and quantization index modulation (QIM) has been proposed that enables embedding of the watermark within an angle of the wavelet's sub-bands. To minimize the degradation effects of the watermark, these sub-bands were selected from frequency ranges where little speaker-specific information was available (500-3500 Hz and 6000-7000 Hz). Experimental results on the TIMIT, MIT, and MOBIO speech databases show that the degradation results for speaker verification and identification are 0.39 and 0.97 %, respectively, which are negligible. In addition, the proposed watermark technique can provide the appropriate fragility required for different signal processing operations.

“…This paper have used the idea in [11,12] to propose a new trend for anti-spoofing attack in speaker recognition. The main idea is that the watermark is embedded in speech signal at transmitter side can be applied for checking genuinely of the speaker in receiver side.…”

Section: Introductionmentioning

confidence: 99%

Digital speech watermarking for anti-spoofing attack in speaker recognition

2014 Ieee Region 10 Symposium

Doraisamy

et al. 2014

This paper presents new method for improving the security of speaker recognition in case of spoofing attack. In the proposed technique, digital speech watermarking has been applied on speech signal to increase robustness. To achieve this purpose, watermark is embedded in claimed signal at transmission side and then it is sent through the unsecure channel. In receiver side, watermark is extracted as proof of authentication. The results shows that digital speech watermarking can successfully apply for anti-spoofing attack purposes because the quality of the speech signal is not significantly degraded by watermark.