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中文摘要：
基于语义的数字水印算法研究是当前数字音频内容管理领域的热点问题，该文设计基于统一内容定位技术的音频语义标引框架，建立数字音频语义水印模型。提出了基于RBF神经网络的双重语义水印算法，该算法用RBF神经网络自适应选择水印嵌入的最佳音频片段，用小波变换提取所选音频片段的近似分量和细节分量，分别在两种分量中嵌入不同的语义信息，形成双重语义水印，实现语义信息和原始音频信号的一体化传输。根据语义水印信息的不同属性描述，实现音频资源的有效检测与监督。实验结果表明，当嵌入信息量较大的语义水印时，该算法仍有较好的鲁棒性和不可听性。
英文摘要：
The researches on digital watermarking algorithm based on semantics are hot issues in the field of audio content management. The indexing method of semantic management for audio watermarking based on uniform content locator （UCL） is introduced, and a dual watermarking algorithm based on radical basis function neural network （RBFNN） is proposed. In semantic watermarking model, RBFNN is used to adaptively select the best embedding place of watermarking in the audio data segment, and the wavelet transform is also adopted to extract the approximate weight and the detail component of the selected audio segment. The different audio indexing information as dual semantic watermarking are embedded into the corresponding audio signal, and the constructed dual semantic watermarking model can realize the integration transmission target with semantic information and original audio signal. Furthermore, synchronous code technology is utilized to solve the problem of effective watermarking detection and monitoring. The results show that the proposed strategy can bring excellent robustness and non-auditory while the embedded watermarking is semantic information with large amount of information.
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