基音周期是语音信号最重要的参数之一。
Pitch period is one of the most important parameters in speech signal.
浊音语音可以看作是慢变化的基音周期波形的连接。
Voiced speech is interpreted as a concatenation of slowly evolving pitch cycle waveforms.
基音周期变换是文—语转换和语音转换的重要内容。
Pitch modification is an important part in text-to-speech synthesis and voice conversion.
语音信号序列可以看成是基音周期经整数倍延时后叠加而成。
A vocal signal sequence is treated as that is formed by piling up pitch periods after varying integer delay time.
本文提出了一种新的检测基音周期的方法：“面积差函数法”。
In this paper, we present a new method, which is entitled "the Function of Area Difference", to detect the pitch period of speech signal.
并探讨语音识别在硬件上的实现以及基音周期估值等具体问题。
And probe into the problem of how to project a speech recognition system base on the hardware, also the problem of pitch estimation.
本文提出了一种适用于低速率语音编码系统的基音周期量化算法。
This paper proposed a pitch quantization method for low bit-rate speech coding systems.
基音周期的确定是语音处理领域中的一个尚未完全解决的基本问题。
To get the pitch of a speech remains an unsolved but basic problem in the field of speech signal process.
不同的语音音调主要体现在语音的基音周期和共振峰频率的差别上。
The different pitch and the different formant frequency decide the different pitch-scale.
实验表明，在信噪比较低的情况下，该法也能较精确的检测基音周期。
Through simulation experiments, it is shown that it behaves more robustly and can detect pitch more accurately at low signal-to-noise ratio.
该方法先将帧长和帧率都限制为基音周期的整数倍，即基音同步算法；
The proposed method restricted the frame length and frame shift to multiples of pitch period, called pitch synchronous algorithm;
MBE模型的基音周期搜索算法存在着运算量大，抗噪性能一般等缺点。
The algorithm for pitch period search with MBE model is complex in calculation and low flexible.
中心削波法是用来去除声道影响，以获得更准确的基音周期的一种方法。
Center clipping is a method, which used to wipe off the effect of track, in order to acquire a more exact pitch period.
该算法采用频域分块估计候选基音周期的范围，提高了算法的计算速度。
The proposed algorithm adopts frequency partition to estimate the range of pitch period, improving the computational speed.
为了实现甚低码率下的透明质量语音编码，提出了一种基音周期估计算法。
A kind of robust pitch estimation algorithm is presented for parametric speech coding with transparent quality at very low bit rate.
论文在此法的基础上，提出了一种基于时域自相关平方函数的基音周期估计方法。
So the paper brings forward a method of pitch estimation in time-domain based on correlated square function.
阐述了一种新的基于语音线性预测模型和经典自相关函数法的基音周期检测算法。
In this paper, a new pitch detection method based on classical autocorrelation function is proposed.
本文详细讨论了混合激励线性预测(MELP)的基音周期估计算法及其改进算法。
This paper discusses in detail the pitch detection algorithm of Mixed Excitation Linear Prediction (MELP) and an improved algorithm.
所使用的参数是：信号的短时幅度与能量、一阶和二阶过零率、自相关函数及基音周期等。
The involved parameters are short-time amplitude and energy, lst-and2nd-order zero-crossing rate, autocorrelation function and pitch period.
研究结果表明，小波分析对语音基音周期的检测是非常有效的，对语音压缩基本可达到满意的程度。
The study result shows that it is efficient to apply Wavelet Analysis on determining pitch periodicity and the experiment of applying Wavelet Analysis on speech coding basically achieves our goals.
针对语句后部的变调和基音频率的衰减，采用改进的自相关函数计算方法增强快变基音周期的跟踪。
We adopt improved computation of autocorrelation function for the case of fo change in the end of sentences, and realize accurate tracking to rapidly changed pitch.
同时又采用了滑动窗的方法，使得对基音周期不规则的不平稳的语音段进行基音周期估计时的误差减小。
In the same time, a sliding pitch analysis window method is used, so it can reduce the pitch detection error in non-stationary speech segments with irregular pitch.
这种算法不仅能够跟踪快变的基音周期，增强不规则脉冲时基音周期的估计；还能够鲁棒地估计陡变的基音周期。
The algorithm can not only track rapidly changed pitch, and enhance pitch estimation with irregular pulse, but also make robust estimation of sharply changed pitch.
用合适的状态空间邻近矢量进行非线性局部分析，即使没有基音周期估计，短时预测器同样能建立长时相关性模型。
With an appropriate state space neighbour for the nonlinear local analysis, the short_delay predictor is also able to effectively model the long_term correlation without pitch estimation.
为了在任意采样率下都可以高效、准确地进行基音周期提取，提出基于归一化幅度差平方和函数的基音周期提取算法。
A pitch tracking algorithm was developed based on the normalized sum of the magnitude difference square function (SMDSF) for accurately estimating speech pitch at any sample rate in real time.
介绍了该算法的设计思想和实现过程，并给出代表性的实验结果，将其结果与MBE算法所检测到的基音周期进行比较。
The implementation process and the designing idea of the arithmetic were described in detail, and the representative experiment results were compared with that obtained by MBE arithmetic.
然后根据这一轨迹对语音信号进行“基音调整”，将原始的、具有时变基音周期的信号转化为一个具有恒定基音周期的信号。
Then the speech signal is pitch adjusted according to this pitch contour, where the original signal with time varying pitch period is converted to a signal of constant pitch period.
相对于正常语音来说，耳语音在公共场合的信噪比较低，而且没有基音周期，共振峰不明显，所以耳语音增强具有一定的难度。
The SNR in public environment of whispered speech is lower than normal speech and the former hasn't pitch period and its formants are not obvious, so whispered speech enhancement is harder.
提出一种变长分帧的方法。为了较理想的合成出特定人的自然语音，采用变长分帧方法对特定人的自然语音的四声提取基音周期序列。
For the ideal synthesis, USES a method of changing the long of frame to get pitch periods of given people natural four tones.
提出一种变长分帧的方法。为了较理想的合成出特定人的自然语音，采用变长分帧方法对特定人的自然语音的四声提取基音周期序列。
For the ideal synthesis, USES a method of changing the long of frame to get pitch periods of given people natural four tones.
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