修正倒谱和动态规划的基频估计算法

基音频率是语音信号处理中的一个重要参数。倍频、半频错误以及清浊音判决的可靠性等问题一直是基频估计中的难点问题。在对语音信号的倒谱进行适当修正的基础上，提出了一种高精度的基频估计算法。该算法根据倒谱、短时能量和短时过零率在清音段和浊音段的不同表现，构造了一个清浊音判决函数，大大提高了清浊音判决精度；然后利用动态规划技术进行基频跟踪。在构造代价函数时．充分考虑了基频连续性的影响，从而使该算法既能有效地避免倍频和半频错误，又能体现出基频的自然加倍和减半。通过与现有的几种效果较好的方法进行对比实验，结果表明该算法具有准确率高、基频轨迹平滑的优点，利用该算法得到的基频轨迹基本不需要进行后期平滑处理。

A modified cepstrum-based algorithm for fundamental frequency estimation using dynamic programming

Fundamental frequency （F0） is a key parameter in speech signals processing. Pitch doubling, pitch halving and the reliability of voicing decision are the most difficult problems in the estimation of fundamental frequency. An algorithm based on the modified cepstrum is proposed for the estimation of the fundamental frequency （F0） of speech signals Voicing decisions are made by using a decision function composed of cepstral peak, zero-crossing rate, and energy of short-time segments of speech signals. An accurate voiced/unvoiced classification is obtained based on this decision function. Then a dynamic programming method is used to realize pitch tracking. The consecution of F0 is considered sufficiently in the cost function. The proposed algorithm can avoid the problem concerning with pitch doubling and pitch halving effectively, as well as preserve the natural doubling and halving of F0. The comparing experiments with several other well-known methods show that the algorithm in this paper has some desirable advantages such as high accuracy and smooth F0 contour, which needs no postsmoother.