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A de-noising algorithm for voice recognition with low SNR

机译:低信噪比的语音识别降噪算法

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Voice recognition technology is very important for prevention of identity crimes and cybercrimes because voice contains a lot of personal information. In this research, we propose a voice recognition system which consists of two stages of the feature extraction and identification. In feature extraction, noise directly affects the reason of feature extraction. Therefore, how to effectively remove noise is a special important study voice recognition system. Voice signal will be unavoidably affected by the interference of noise in the process of generation and transmission, thus resulting in a decline in the recognition rate of the system. When someone now enroll and use themselves voiceprint with noise to verify their identity by our presented system, the next time only use an app to access online services or phone, this security recognition system will help online system protect users account and reduce the chances of scammers accessing users account and information. The results of experiments, when SNR are -5, 0 and 5, the recognition rate of our proposed system can reach 80.1%, 86.2% and 90.4%, respectively. This research fits to the key approaches to prevent cybercrimes.
机译:语音识别技术对于预防身份犯罪和网络犯罪非常重要,因为语音包含大量个人信息。在这项研究中,我们提出了一种语音识别系统,该系统包括特征提取和识别的两个阶段。在特征提取中,噪声直接影响特征提取的原因。因此,如何有效地去除噪声是语音识别系统研究的重要课题。语音信号在生成和传输过程中不可避免地会受到噪声干扰,从而导致系统的识别率下降。现在,当有人通过我们提出的系统注册并使用带有噪音的自己的声纹来验证其身份时,下次仅使用应用程序访问在线服务或电话时,此安全识别系统将帮助在线系统保护用户帐户并减少欺诈者的机会访问用户帐户和信息。实验结果表明,当SNR为-5、0和5时,我们提出的系统的识别率分别可以达到80.1%,86.2%和90.4%。这项研究符合预防网络犯罪的关键方法。

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