One is the relation between long - term prediction and short - term prediction , another is the difference between the surd and sonant in linear prediction , robust of message source encoding is also researched . 3 清音和浊音在安排短时预测和长时预测方面的问题；短时预测和长时预测相互包容性问题；提高算法的鲁棒性等方面问题。
2.
Because the speech signal is periodicity at sonant which vocal cords surge in low frequency and similarity to white noises at surd , the pitch can be detected in traditional way through the correlation operation without the speech produce model 在人类语音的浊音段，声带发生较低频率的振荡，语音信号呈明显的准周期性，而在清音段，语音信号则类似于白噪声。
3.
Experimental result shows that for sonant part of speech signal , 3 ~ 5 common ridges is enough to describe the main characteristics . signal compression is achieved by choosing proper way to represent the ridge information and use it to reconstruct the original signal 在信号重建过程中，选择合适的方法用少量数据来描述起关键作用的参数，并用这些参数来重建信号，可以达到信号压缩的目的。
4.
But it is not the same with surd or the alternation of sonant and surd . on the base of the acoustics , a whole linear time - varying discrete speech produce model is established through anatomising the factors including track , driving source and lip eradiation the mechanism of speech in this paper , and we draw a conclusion that the time between glottal closure is pitch period 本文从声学理论出发，剖析了语音产生的机理，综合考虑声道、激励源和嘴唇辐射三方面的因素，建立了一个完整的、线性的和时变的语音产生的离散系统模型，得出两次声门闭合事件之间的时间间隔就是基音周期的结论。
5.
According to difference of speech waveform between transition segment and non - transition segment , dividing between sonant is researched using waveform cross correlation . a method of syllable segmentation is presented based on waveform cross - correlation . ( 2 ) pitch detection of speech signals 为解决浊音之间的分割问题，本文根据语音中过渡段与非过渡段语音波形的差异，利用波形互相关性进行了研究，提出了基于波形互相关性的音节分割方法，并进行了实例分析。
6.
In accordance with chaotic essence of speech signals , syllable segmentation in continuous speech is researched by fractal theory . an approach of syllable segmentation using variance fractal dimension is proposed , its performance is analyzed in detail . the method can discriminate between voiced and unvoiced , between surd and sonant , but it can hardly discriminate between sonant 本文根据语音信号的混沌本质，利用分形理论研究了汉语连续语音中的音节分割问题，提出了基于方差分形维数的音节分割方法，并详细分析了该方法的性能，它能很好地解决了无声与有声、浊音与清音间的分割问题，但很难解决浊音间的分割问题，当浊音相连且过渡段较短时，该方法无法实现它们之间的分割。
