语音欺骗检测方法的研究现状及展望
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陆军工程大学指挥控制工程学院,南京,210007

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国家自然科学基金(61471394,62071484)资助项目;江苏省优秀青年基金(BK20180080)资助项目。


Speech Anti-spoofing: The State of the Art and Prospects
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College of Command and Control Engineering, Army Engineering University, Nanjing, 210007, China

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    摘要:

    语音欺骗是指通过录音、语音合成(Text-to-speech, TTS)、语音转换(Voice conversion, VC)等手段,将一段非法的、未经过自动说话人验证(Automatic speaker verification, ASV)系统认证的声音进行“修改仿冒”,以达到通过ASV系统检测的目的。随着人工智能和语音欺骗技术的发展,ASV系统在安全性方面遇到了严峻的挑战。检测输入ASV系统的语音的真实性,防止欺骗语音通过ASV的验证以提高ASV系统的安全性,是近年来语音领域研究的一个热点问题。国内外学者的最新研究从声学特征选取、识别模型选择等角度出发,探索了不同的语音欺骗方法对ASV系统的影响,并深入研究了相应的语音欺骗检测技术,在一定程度上提高了ASV系统的防欺骗性能。本文介绍了语音欺骗的基本方法,给出了语音欺骗检测的框架和典型声学特征,分两大类别总结了语音欺骗检测的主要方法和最新进展,梳理了目前语音欺骗检测中仍然存在的若干技术问题,并对语音欺骗检测技术的发展方向进行了展望。

    Abstract:

    Speech spoofing refers to the technology of counterfeiting an illegal speech without the authentication by automatic speaker verification (ASV) system to the speech of a legally authenticated speaker by ASV through recording, text-to-speech, voice conversion and other means, so as to achieve the goal of passing the ASV system. With the development of artificial intelligence and speech anti-spoofing methods, ASV systems have encountered severe challenges in security. It is a hot topic in the field of speech research in recent years to detect the authenticity of the speech input to the ASV system and to prevent spoof speech from passing the verification of ASV to improve the security of the ASV system. The latest research of scholars at home and abroad explores the influence of different speech spoofing methods on ASV system from the perspective of acoustic feature and recognition model, and further studies the corresponding speech anti-spoofing technology, which improves the anti-spoofing ability of ASV systems to a certain extent. This paper summarizes the latest methods of speech spoofing to ASV systems and the latest anti-spoofing methods, focusing on the state-of-the-art research results around the world, and prospects the development direction of speech anti-spoofing technology.

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张雄伟,李嘉康,孙蒙,郑琳琳.语音欺骗检测方法的研究现状及展望[J].数据采集与处理,2020,35(5):807-823

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  • 收稿日期:2020-05-20
  • 最后修改日期:2020-07-22
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  • 在线发布日期: 2020-10-22