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Development and application of composite logistics functions to improve the speed of training of wavelet neural networks in speech recognition systems

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Title: Development and application of composite logistics functions to improve the speed of training of wavelet neural networks in speech recognition systems

Authors: Dmitry Ivanovich Popov, Artem Vladimirovich Gapochkin

Journal: ARPN Journal of Engineering and Applied Sciences

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
X 2020-07-01 2021-06-30

Publisher: Khyber Medical College, Peshawar

Country: Pakistan

Year: 2016

Volume: 11

Issue: 1

Language: English

Categories
Computer Science (14978) Signal Processing (1285) Speech Recognition (82) Machine Learning (3478) Artificial Intelligence (6625)

Abstract

This article suggests a new approach to handling voice communications, based on the joint application of wavelet analysis and neural networks. One of the most effective methods of speech signals currently performing wavelet analysis. The use of large-scale analysis allows estimating the speech signal as from the point of view of the spectrum and temporal variation. The advantages of wavelet neural network for the multi-layer network.

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