基于分类算法的语音识别

O. Mamyrbayev, N. Mekebayev, M. Turdalyuly, N. Oshanova, Tolga Ihsan Medeni, A. Yessentay
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引用次数: 11

摘要

本文讨论了基于机器学习方法的语音人格识别问题的分类算法。我们在语音预处理过程中使用了MFCC算法。为了解决这一问题,对五种分类算法进行了比较分析。在第一次实验中,确定了支持向量法- 0.90,多层感知器- 0.83,效果最好。在第二个实验中,使用鲁棒尺度方法提出了一个精度为0.93的多层感知器用于个人识别。因此,为了解决这个问题,考虑到语音信号的特殊性,可以使用多层感知器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Voice Identification Using Classification Algorithms
This article discusses the classification algorithms for the problem of personality identification by voice using machine learning methods. We used the MFCC algorithm in the speech preprocessing process. To solve the problem, a comparative analysis of five classification algorithms was carried out. In the first experiment, the support vector method was determined — 0.90 and multilayer perceptron — 0.83, that showed the best results. In the second experiment, a multilayer perceptron with an accuracy of 0.93 was proposed using the Robust scaler method for personal identification. Therefore, to solve this problem, it is possible to use a multi-layer perceptron, taking into account the specifics of the speech signal.
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