Speech Profile Recognition by Fourier Spectral, FFNN and ANFIS Techniques

被引：0

作者：

Balabanova, Ivelina ^{[1
]}

Georgiev, Georgi ^{[1
]}

机构：

[1] Tech Univ Gabrovo, Dept Commun Equipment & Technol, Gabrovo, Bulgaria

来源：

2021 29TH NATIONAL CONFERENCE WITH INTERNATIONAL PARTICIPATION (TELECOM) | 2021年

关键词：

voice profiles; recognition; FFT windowing; artificial neural networks; adaptive neuro-fuzzy systems; CONVOLUTIONAL NEURAL-NETWORKS;

D O I：

10.1109/TELECOM53156.2021.9659793

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a combined approach for recognition of speech profiles based on FFT windowing, Feed-Forward Neural Networks (FFNN) and Adaptive Neuro-Fuzzy Interface Systems (ANFIS). By using spectral analysis of the speech of physical entities, there have been carried out feature extraction during application of Hamming, 4 Term B-Harris, Flat Top and Hanning windows. Individual informative sets (data sets) have been specified for the employed mathematical recognition apparatuses. A FFNN model has been synthesized during implementation of Scaled Conjugate Gradient (SCG) training for the purpose of speech profiles recognition with attained accuracy of 93.50 %. There has been selected neuro-fuzzy classifier in accordance with Hybrid learning algorithm and Pi shaped membership function of input variables. During testing of selected.NFIS model there has been established a 100.00 % accuracy in speech profiles recognition.

引用

页码：100 / 103

页数：4

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