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Digital speech watermarking to enhance the security using speech as a biometric for person authentication

机译:数字语音水印可使用语音作为人员身份验证的生物识别技术来增强安全性

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This work presents the modules for enhancing the security of speaker authentication by embedding the watermark in a speech signal. Speaker is authenticated by speech as well as the extracted watermark from the watermarked speech. Firstly, the speech signal is converted into frames, and discrete wavelet transform is applied to each frame, and it is preferable to embed the watermark in detail coefficients. The segment for embedding the watermark is appropriately chosen based on the energy calculations. The approximation and the modified detail coefficients are used to generate the watermarked speech by inverse discrete wavelet transform. Imperceptibility of the watermark in a watermarked speech is purely depending on the embedding of the watermark. In the receiver, the watermarked speech will undergo wavelet decomposition, and the watermark bits are extracted from the detail coefficients and appropriately transformed into watermark speech/image. The performance the work is evaluated by using the metrics such as Peak signal to noise ratio (PSNR) between original watermark and extracted watermark, PSNR between original speech and watermarked speech and Bit error rate (BER) and Perceptual evaluation speech quality (PESQ). Speaker identification system is assessed by using extraction of the perceptual features and application of features to develop the models for the set of utterances about the speaker during the training phase of the work. Testing is done by applying the original and watermarked speech utterances to the feature extraction phase, followed by we have the testing phase which is used for computing the accuracy. Accuracy is 98.2% for the speaker identification with the set of original test utterances and 98.1% with watermarked set of test utterances and it is observed that there is the marginal difference in accuracy for using speech as a watermark. It is 97.85% for using the image as a watermark. Cover speech signals and watermark speech used in our work are continuous speech utterances chosen from “TIMIT” speech database. Image watermark is the Quick response (QR) code for the LOGO. This work also emphasizes the effectiveness of the algorithm in providing robustness for copyright protection to ownership of the data and authenticating persons using speech as a biometric.
机译:这项工作提出了通过将水印嵌入语音信号中来增强说话者身份验证安全性的模块。通过语音以及从带水印的语音中提取的水印对说话者进行身份验证。首先,将语音信号转换成帧,并且将离散小波变换应用于每个帧,并且优选将水印嵌入细节系数中。基于能量计算适当地选择用于嵌入水印的片段。近似值和修改后的细节系数用于通过逆离散小波变换生成水印语音。水印语音中水印的不可感知性完全取决于水印的嵌入。在接收机中,带水印的语音将进行小波分解,并且从细节系数中提取水印比特,并将其适当地转换为水印语音/图像。使用原始水印和提取的水印之间的峰值信噪比(PSNR),原始语音和水印语音之间的PSNR,误码率(BER)和感知评估语音质量(PESQ)等指标来评估作品的性能。通过使用感知特征的提取和特征的应用来评估说话者识别系统,以在工作的训练阶段针对说话者的话语集开发模型。通过将原始语音和带水印的语音应用到特征提取阶段来进行测试,然后进行测试阶段以计算准确性。一组原始测试话语的说话人识别准确度为98.2%,带有水印的测试话语集准确度为98.1%,观察到使用语音作为水印的准确度存在边际差异。使用图像作为水印的比例为97.85%。我们工作中使用的掩体语音信号和水印语音是从“ TIMIT”语音数据库中选择的连续语音。图像水印是LOGO的快速响应(QR)代码。这项工作还强调了该算法在为数据所有权提供版权保护的鲁棒性以及使用语音作为生物特征认证人员身份方面的有效性。

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