论文标题
语音文件本地功能调查的一种新方法
A New Method Towards Speech Files Local Features Investigation
论文作者
论文摘要
最近，人们对语音文件的本地特征的研究产生了越来越多的兴趣。据指出，所使用的扬声器语言的许多基本特征可以以语音信号的形式出现。传统仪器 - 短傅里叶变换，小波变换，哈达玛德变换，自相关等，类似于该语言的所有特定属性。在本文中，我们建议一种新的方法来探索此类特性。源信号由具有有限集的新的值近似。然后，我们在这些近似值的底座上构造了一个固定大小的向量序列。对生产向量的分布进行检查为说明语音文件本地特征提供了一种新方法。最后，开发的技术应用于自动区分语音文件中使用的两种已知语言的问题。为此，消耗了简单的神经网。
There are a few reasons for the recent increased interest in the study of local features of speech files. It is stated that many essential features of the speaker language used can appear in the form of the speech signal. The traditional instruments - short Fourier transform, wavelet transform, Hadamard transforms, autocorrelation, and the like can detect not all particular properties of the language. In this paper, we suggest a new approach to the exploration of such properties. The source signal is approximated by a new one that has its values taken from a finite set. Then we construct a new sequence of vectors of a fixed size on the base of those approximations. Examination of the distribution of the produced vectors provides a new method for a description of speech files local characteristics. Finally, the developed technique is applied to the problem of the automatic distinguishing of two known languages used in speech files. For this purpose, a simple neural net is consumed.
