F0 Modification via PV-TSM Algorithm for Speaker Anonymization Across Gender
F0 Modification via PV-TSM Algorithm for Speaker Anonymization Across Gender
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DOI：
10.23919/apsipaasc55919.2022.9979993
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发表时间：
2022-11
期刊：
影响因子：
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通讯作者：
Candy Olivia Mawalim;S. Okada;M. Unoki
中科院分区：
文献类型：
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作者：
Candy Olivia Mawalim;S. Okada;M. Unoki
说话人匿名化的发展是为了在保护个人身份信息的同时保留语音中的其他封装信息。语音隐私挑战(VPC)中定义了用于评估说话人匿名化的数据集、指标和协议。然而，现有的隐私度量侧重于评估一般说话人的个性匿名化，这是由一个x向量表示的。本研究旨在探讨匿名化对性别知觉的影响。了解匿名化是如何引起性别转变的，对于说话人匿名化的各种应用是至关重要的。我们提出了基于相位声码器时间尺度修改的跨性别说话人匿名方法(PV-TSM)。随后，除了VPC评估之外，我们还开发了一个性别分类器来评估说话人的性别匿名化。客观评价结果表明，该方法能够成功地实现性别匿名化。此外，在保持语音清晰度的同时，我们提出的方法在保持语音清晰度的同时，在匿名化说话人个性方面优于基于信号处理的基线方法。
Speaker anonymization has been developed to protect personally identifiable information w hile r etaining other encapsulated information in speech. Datasets, metrics, and protocols for evaluating speaker anonymization have been defined in the Voice Privacy Challenge (VPC). However, existing privacy metrics focus on evaluating general speaker individuality anonymization, which is represented by an x-vector. This study aims to investigate the effect of anonymization on the perception of gender. Understanding how anonymization caused gender transformation is essential for various applications of speaker anonymization. We proposed speaker anonymization methods across genders based on phase-vocoder time-scale modification (PV-TSM). Subsequently, in addition to the VPC evaluation, we developed a gender classifier toe valuate a speaker's gender anonymization. The objective evaluation results showed that our proposed method can successfully anonymize gender. In addition, our proposed methods outperformed the signal processing-based baseline methods in anonymizing speaker individuality represented by the x-vector in ASVeval while maintaining speech intelligibility.