Bio-inspired voice evaluation mechanism

被引:22
|
作者
Polap, Dawid [1 ]
Wozniak, Marcin [1 ]
Damasevicius, Robertas [2 ]
Maskeliunas, Rytis [2 ]
机构
[1] Silesian Tech Univ, Inst Math, Kaszubska 23, PL-44100 Gliwice, Poland
[2] Kaunas Univ Technol, Fac Informat, Barsausko 59, LT-51423 Kaunas, Lithuania
关键词
Audio signal visualization; Feature extraction; Neural classifier; Heuristic algorithm; Fourier transformation; Gabor transformation; Wavelet transformation; Laurent transformation; DECISION-MAKING; CLASSIFICATION; DIAGNOSIS; DISEASE; SPEECH; RECOGNITION; PERFORMANCE; ALGORITHM; NETWORKS; FEATURES;
D O I
10.1016/j.asoc.2019.04.006
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Decision support systems become a very important part of our lives. Technologies make them applicable almost everywhere. These systems can simplify solutions to the numerous problems, speed up analysis of the results of medical research and contribute to the rapid classification of input patterns. Practical applications may not only contribute to efficient technology, but also improve important aspects of our lives. In this article, we propose a model of decision support system for speech processing. Proposed mechanism can be used in various applications, where voice sample can be evaluated by the use of the proposed methodology. The proposed solution is based on analysis of the speech signal through the developed intelligent technique in which the signal is processed by the composed mathematical transform cooperating with bio-inspired algorithm and spiking neural network to evaluate possible voice problems. A novelty of our idea is the approach to the topic from a different side, because graphical representations of audio signals and heuristic methods are composed for feature extraction. The results are discussed after extensive comparisons in terms of advantages and disadvantages of the proposed approach. As a part of the conducted research, we demonstrated which transformations and heuristic algorithms work better in the process of voice analysis. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码:342 / 357
页数:16
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