Kalman Filter Approach for Pitch Determination of Speech Signals
Kalman Filter Approach for Pitch Determination of Speech Signals
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用于语音信号音调确定的卡尔曼滤波器方法
DOI：
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发表时间：
2006
期刊：
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通讯作者：
U. Orguner
中科院分区：
文献类型：
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作者：
O. Salor;M. Demirekler;U. Orguner
本文提出了一种有效的语音信号基音周期确定算法。语音信号的音调曲线在语音的浊音和清音过渡区中不表现出时间上的突然变化。根据这一特性，卡尔曼滤波器已被用于语音的音高确定类似的方式，它被用于目标跟踪问题。在MELP语音编码算法中，作为基音周期确定的第一步，利用基于自相关法的整数基音周期计算，得到了卡尔曼滤波器的测量值。卡尔曼滤波器进行先验估计，其取决于音调周期在时间上的一般行为，并且使用测量来更新该估计以获得后验估计。所提出的方法提供了一个降低的计算复杂度的音高确定，因为自相关搜索是只在门控体积的卡尔曼滤波器，因此没有音高加倍检查是必需的。它也不需要任何分数音调计算。用这种方法得到的基音周期与MELP算法中确定的基音周期进行了比较，并观察到得到了相当的结果。
In this paper, an efficient algorithm for pitch determination of speech signals is presented. Pitch curves of speech signals do not exhibit sudden changes in time in voiced and voicedunvoiced transition regions of speech. Depending on this property, Kalman Filter has been used for pitch determination of speech similar to the way it is used in target tracking problems. The measurement for the Kalman Filter is obtained by using the integer pitch calculation based on autocorrelation method, which is used as the first step of pitch determination in MELP speech coding algorithm. Kalman Filter makes an a priori estimate, which depends on the general behaviour of the pitch period in time and this estimate is updated using the measurement to obtain an a posteriori estimate. The proposed method provides a reduction in the computational complexity of pitch determination since the autocorrelation search is made only inside the gating volume of the Kalman Filter and hence no pitch doubling check is required. It also does not need any fractional pitch computations. The pitch periods obtained using this method have been compared to those determined in MELP algorithm and it has been observed that comparable results have been obtained.