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Blind Detection of Electronic Voice Transformation with Natural Disguise

机译:用自然伪装盲检测电子语音变换

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Electronic voice transformation with natural disguise ability is a common operation to change a person's voice and conceal his or her identity, which can easily cheat human ears and automatic speaker recog-nition(ASR) systems and thus presents threaten to security. Till now, few efforts have been reported on detection of electronic transformation, which aims to distinguish disguised voices from original voices. Therefore in this paper we investigate the principle of electronic voice transformation, and propose a blind detection approach using MFCC(Mel Frequency Cepstrum Coefficients) as the acoustic features and VQ-SVM (Vector Quantization-Support Vector Machine) as the classification method. By extensive experiments, it is demonstrated to have classification accuracy higher than 98% in most cases, indicating that the proposed approach has good performance and can be used in forensic applications.
机译:具有自然伪装能力的电子语音转换是改变一个人的声音并隐瞒他或她的身份的常见操作,这可以轻松欺骗人类的耳朵和自动扬声器Recog-nition(ASR)系统,从而威胁到安全。到目前为止,还有很少的努力检测电子转换,旨在区分原始声音的伪装声音。因此,在本文中,我们研究了电子语音变换的原理,并提出了使用MFCC(MEL频率谱系数)作为声学特征和VQ-SVM(向量量化 - 支持向量机)作为分类方法的盲检测方法。通过广泛的实验,在大多数情况下,将分类精度具有高于98%的分类精度,表明所提出的方法具有良好的性能,可用于法医应用。

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