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Robust speaker recognition for e-commerce system

机译:电子商务系统的可靠说话人识别

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摘要

In banking system of e-commerce, where privacy and authentication are more important and voice based authentication is preferred, telecommunication plays vital role by enabling users to interact remotely and verify their identities. The design of such robust speaker recognition system can have various problems related to combined optimization of a number of processes like front-end noise removal, auditory parameter extraction and the speech modeling/recognition paradigm. In this paper we examine these front-end noise reduction/removal techniques with focus on development of a generic speech improvement method based on hybrid echo filter to particularly handle speech signals that travel through telephonic channel. Firstly noised telephonic signals are subjected to spectral subtraction and accuracy of correctly denoised samples is obtained which is 76%. The resultant signals are further improved by applying echo filter technique which dramatically increases the accuracy up to 83.5%. Achieved results are highly significant as they improve accuracy of the system as compared to contemporary work in the area.
机译:在电子商务银行系统中,隐私和身份验证更为重要,并且首选基于语音的身份验证,电信通过使用户能够远程交互并验证其身份来发挥至关重要的作用。这种鲁棒的说话者识别系统的设计可能具有与诸如前端噪声去除,听觉参数提取和语音建模/识别范例的许多过程的组合优化有关的各种问题。在本文中,我们重点研究了基于混合回声滤波器的通用语音改进方法的开发,以特别处理通过电话通道传播的语音信号,从而解决了这些前端降噪/消除技术。首先,对噪声的电话信号进行频谱相减,获得正确去噪的样本的准确度为76%。通过应用回波滤波器技术可以进一步改善所得信号,该技术可将精度大幅提高至83.5%。与该地区的当代工作相比,所取得的成果非常重要,因为它们提高了系统的准确性。

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