Semi-fragile digital speech watermarking for online speaker recognition

Abstract

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.

Speech Watermarking using a Hybrid Strategy of both Empirical Mode Decomposition and Singular Value Decomposition

“…Figure (6) shows the original speech signal and its spectrogram, first IMF and its spectrogram, SVD watermark image and block-based SVD watermark image. Figures (7) and (8) show the watermarked speech signal in the absence and presence of different attacks and its spectrogram respectively. Figure (9) shows the extracted watermarks, using EMD and SVD in the absence and presence of different attacks.…”

Robust Digital Speech Watermarking For Online Speaker Recognition

“…Therefore, by using two free auxiliary parameters and which are stated in (14), | 1, , is expressed by (15). Consider the following:…”

“…However, the speaker identification and verification performance can be decreased [5,6,12,13]. Therefore, some researchers apply semifragile watermarking to reduce this impact on recognition performance [14,15]. Although semifragile watermarking techniques can be used for tamper detection, a requirement is still needed for robust watermarking techniques to protect the ownership.…”

Optimization of a Blind Speech Watermarking Technique against Amplitude Scaling

“…However, the quantization strategy suffers from amplitude scaling. To rectify this problem, rational dither modulation (RDM) [3] was proposed to enhance the robustness of quantization index modulation (QIM) [4,5]; however, it degraded the imperceptibility of the watermarked signal. Hence, hyperbolic RDM [6] was proposed to improve the robustness against power law and gain attacks.…”

“…Generally, speech watermarking should preserve the identity of the speaker, which is important for certain security applications [12,13]. To preserve speaker-specific information, some investigations have been conducted to embed the watermark into special frequency subbands that have less speaker-specific information [5,14,15]. Further discussion can be found in [16].…”