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Robust speaker recognition for e-commerce system

机译:电子商务系统的强大扬声器识别

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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,隐私和认证更重要,并且基于语音认证是首选,电信通过使用户远程交互并验证其身份来扮演重要作用。这种稳定扬声器识别系统的设计可以具有与组合优化多个过程的各种问题,如前端噪声去除,听觉参数提取和语音建模/识别范例。在本文中,我们研究了这些前端降噪/去除技术,重点是基于混​​合回波滤波器的通用语音改进方法的开发,特别地处理穿过电话通道的语音信号。首先,发出直拨电话信号经受光谱减法,获得正确的去噪样品的精度,其为76%。通过应用回声滤波器技术进一步提高了所得信号,这显着提高了高达83.5%的精度。与该地区当代工作相比,达到的结果非常重要,因为它们提高了系统的准确性。

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