首页> 外文期刊>International journal of computer science and network security >A Pitch Detection Algorithm Based on Windowless Autocorrelation Function and Modified Cepstrum Method in Noisy Environments
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A Pitch Detection Algorithm Based on Windowless Autocorrelation Function and Modified Cepstrum Method in Noisy Environments

机译:噪声环境下基于无窗自相关函数和改进的倒谱方法的基音检测算法

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This paper proposes a new pitch detection algorithm of speech signals in noisy environment. The performance of the cepstrum method is effected due to the formant effect and the presence of spurious peaks introduced in noisy condition. In our proposed method, we firstly employ windowless autocorrelation function instead of its speech signal for obtaining the cepstrum. The windowless autocorrelation function is a noise-reduced version of the speech signal where the periodicity is more apparent with enhanced pitch peak. Secondly the modified cepstrum method is applied to windowless autocorrelation function which utilizes clipping and band pass filtering operation on log spectrum. The performance of the proposed pitch detection method is compared in terms of gross pitch error with the other related methods. Experimental results on male and female voices in white and color noises shows the superiority of the proposed method over some of the related methods under low levels of signal to noise ratio.
机译:提出了一种在噪声环境下语音信号基音检测的新算法。由于共振峰效应和在嘈杂条件下引入的虚假峰的存在,影响了倒频谱方法的性能。在我们提出的方法中,我们首先采用无窗自相关函数代替语音信号来获得倒频谱。无窗自相关函数是语音信号的降噪版本,其中随着音调峰值的增强,周期性更加明显。其次,将改进的倒频谱方法应用于无窗自相关函数,该函数利用对数谱上的削波和带通滤波操作。提出的音高检测方法的性能在总音高误差方面与其他相关方法进行了比较。在白噪声和彩色噪声中男女声音的实验结果表明,在信噪比较低的情况下,该方法优于某些相关方法。

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