匹配两个系列MFCC系数 [英] Matching two series of Mfcc coefficients

问题描述

我已经抽取了2个系列的MFCC系数从由同一讲话内容两个围绕30秒的音频文件。音频文件被记录在来自不同来源的相同的位置。估算应的音频是否包含相同会话或不同的会话。目前，我已经测试这两个MFCC一系列的相关计算，但结果不是很合理。是否有最佳做法，对于这种情况？

I have extracted two series MFCC coefficients from two around 30 second audio files consisting of the same speech content. The audio files are recorded at the same location from different sources. An estimation should be made whether the audio contains the same conversation or a different conversation. Currently I have tested a correlation calculation of the two Mfcc series but the result is not very reasonable. Are there best practices for this scenario?

推荐答案

我有同样的问题，它的解决方案是使用的动态时间规整算法

I had the same problem and the solution for it was to match the two arrays of MFCCs using the Dynamic Time Warping algorithm.

计算MFCCs你现在应该有，为每个两个信号，其中每个元素包含MFCCs一帧（数组的数组）的数组后。第一步是计算每两组MFCCs之间的另一方面，即距离中的每一个元素的一个阵列的每一个元素之间距离（你可以尝试使用的欧氏距离这个）。

After computing the MFCCs you should now have, for each of your two signals, an array where each element contains the MFCCs for a frame (an array of arrays). The first step would be to compute "distances" between every one element of one array and every one element of the other, i.e. distances between every two sets of MFCCs (you could try using the Euclidian Distance for this).

这应该留给你一个2维数组（姑且称之为测距），其中的元素（I，J）再presents在第一信号和第i帧的MFCCs之间的距离第二个信号的第j个帧的MFCCs

This should leave you with a 2-dimensional array (let's call it "dist") where element (i,j) represents the distance between the MFCCs of the i-th frame in the first signal and the MFCCs of the j-th frame of your second signal.

在这个阵列现在可以应用DTW算法：

On this array you can now apply the DTW algorithm:

• DTW（1,1）= DIST（1,1）


• DTW（I，J）=分钟（DTW（ⅰ-1，J-1），DTW（ⅰ-1，j）中，DTW（I，J-1））+ DIST（I，J）。

转口货值为presenting你的两个文件之间的差异是DTW（N，M），其中n = NR。在第一信号，M = NR帧。中的第二个的帧。

The value representing the "difference" between your two files is dtw(n,m), where n = nr. of frames in the first signal, m = nr. of frames of the second one.

有关进一步阅读，本文可能会给你的总体视图应用DTW到MFCCs和的这个presentation 的DTW算法可能也有帮助。

For further reading, this paper might give you an overall view of applying DTW to MFCCs and this presentation of the DTW algorithm might also help.

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