lpc造句
例句与造句
- Dynamic mapping algorithm is also illustrated in details . through the computer simulation to some real short - time voice signal samples using matlab language . the result shows that the recognition efficiency using cepstrum coefficients mapping is better than what made by lpc mapping
实验结果表明，与采用lpc特征相比，采用lpc倒谱特征和动态匹配算法进行短时语音识别，会有较高的识别率；对不同语音信号有特征空间离散度大、易于确定判别门限的特点。 - This paper concerns the basic study of a lpc . firstly , a new method for predicting the leakage of the compressor has been developed and solved by an iterative visual c + + program , the simple analytical and explicit method is shown to provide realistic results which agree with measurements
然后本文建立了迷宫密封泄漏流动的数学模型,在此基础上提出了一种计算密封泄漏量的简化分析的迭代方法,通过与现有方法的对比分析,发现该方法计算精度高,有较好的通用性。 - One is using the autocorrelation function to detect the speech terminal , the other is using the coefficients based on the one - sided autocorrelation sequence to replace the original speech signal and then extract the speech feature to recognize . isolated word recognition experiment based on dtw shows : it can reduce the disturbance of noise effectively and get the high recognition rate . it is of great advantage to apply when snr signal to noise rate is low
对含噪语音在自相关域上进行处理，以其自相关函数值为参数进行端点检测，以基于单边自相关序列的lpc倒谱系数作为语音的特征参数进行语音识别，实验表明：这种方法较好地消除了噪声对语音信号的干扰，并获得了较高的识别率。 - Based on high - dimension space geometry , every speech sample is looked as a point in space . then the speech sample point is extracted feature by lpc , mel - scaled cepstrum analysis or auto correlation - angle . their feature is looked as a point too
基于高维空间几何的思想，把每个样本点和其特征值看作高维空间中的一个点，用线性预测分析、 mel倒谱分析和自相关夹角法对样本点提取特征，然后用点在空间的投影来判别语音和非语音，根据判别结果来比较三种特征提取方法的优劣。 - There are difficulties in noisy speech recognition , especially low signal - to - noise rations are more difficult . this paper describes briefly six methods for speaker - dependent noisy speech recognition isolated words . they are lpc prediction error method , one - side auto - correlation sequence lpc , acoustic front end processing , canonical correlation based on compensation method , combination of features method and increase of poles method . the experimental results show that all the six techniques can improve effectively noisy speech recognition , and the best noisy speech recognition rate is above 80 % when snr 0db
它们是：线性预测误差法，单边自相关线性预测法，语音前端声学处理法，正则相关分析的谱变换补偿方法，特征综合法和同模极点增加法。实验结果表明，这6种方法都有效地提高了噪声环境中语音识别率，其中较好的方法在强噪声环境中信噪比为0db的语音识别率达到80 %以上，为信噪比较低的噪声环境中自动语音识别展现了美好前景。 - It's difficult to find lpc in a sentence. 用lpc造句挺难的
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