Speaker anonymization aims to suppress speaker individuality to protect privacy in speech while preserving the other aspects, such as speech content. One effective solution for anonymization is to modify the McAdams coefficient. In this work, we propose a method to improve the security for speaker anonymization based on the McAdams coefficient by using a speech watermarking approach. The proposed method consists of two main processes: one for embedding and one for detection. In embedding process, two different McAdams coefficients represent binary bits ``0" and ``1". The watermarked speech is then obtained by frame-by-frame bit inverse switching. Subsequently, the detection process is carried out by a power spectrum comparison. We conducted objective evaluations with reference to the VoicePrivacy 2020 Challenge (VP2020) and of the speech watermarking with reference to the Information Hiding Challenge (IHC) and found that our method could satisfy the blind detection, inaudibility, and robustness requirements in watermarking. It also significantly improved the anonymization performance in comparison to the secondary baseline system in VP2020.
翻译:发言人匿名的目的是压制演讲者的个人特性,以保护言论中的隐私,同时保护其他方面的隐私,例如言论内容。匿名的一个有效解决办法是修改麦克阿达姆斯系数。在这项工作中,我们提出一种方法,通过使用语音水标记方法,改善麦卡达姆斯系数的发言者匿名安全。拟议方法包括两个主要过程:一个是嵌入过程,一个是检测过程。在嵌入过程中,两种不同的麦克达姆系数代表了二进制位位数“0”和“1”。水标记演讲随后通过框架位数反转获得。随后,检测过程通过电力频谱比较进行。我们进行了客观评估,参照了2020年语音隐私挑战(VP2020)和与信息隐蔽挑战(IHC)有关的语音标注,发现我们的方法可以满足水标记中的盲点检测、失能和稳健要求。它还大大改进了与VP2020次级基线系统的匿名性功能。