Classification of speech signals is a vital part of speech signal processing *** the advent of speech coding and synthesis,the classification of the speech signal is made accurate and *** methods are considered inaccu...
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Classification of speech signals is a vital part of speech signal processing *** the advent of speech coding and synthesis,the classification of the speech signal is made accurate and *** methods are considered inaccurate due to the uncertainty and diversity of speech signals in the case of real speech signal *** this paper,we use efficient speech signal classification using a series of neural network classifiers with reinforcement learning *** classification of speech signals,the study extracts the essential features from the speech signal using Cepstral *** features are extracted by converting the speech waveform to a parametric representation to obtain a relatively minimized data *** to improve the precision of classification,Generative Adversarial Networks are used and it tends to classify the speech signal after the extraction of features from the speech signal using the cepstral *** classifiers are trained with these features initially and the best classifier is chosen to perform the task of classification on new *** validation of testing sets is evaluated using RL that provides feedback to ***,at the user interface,the signals are played by decoding the signal after being retrieved from the classifier back based on the input *** results are evaluated in the form of accuracy,recall,precision,f-measure,and error rate,where generative adversarial network attains an increased accuracy rate than other methods:Multi-Layer Perceptron,Recurrent Neural Networks,Deep belief Networks,and Convolutional Neural Networks.
Repeated breath cessation during sleep due to the closure of the airway passage is a condition known as obstructive sleep apnea (OSA). Untreated OSA elevates occupational-related fatal incidents, motor vehicle acciden...
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The selection of unvoiced and voiced signals is typically made through the analysis of speech by extracting the desired set of information from the given speech signal. The different approaches for distinguishing betw...
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This manuscript introduces a methodical investigation into the design of left-handed circularly polarized (LHCP) antennas tailored for optimal performance within the framework of Internet of Things (IoT) wireless netw...
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The analysis of average spectral efficiency (ASE) of multi-pulse position modulation (MPPM) scheme with optimal rate adaptation (ORA) and channel inversion with fixed rate (CIFR) adaptation schemes over the gamma-gamm...
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As we are utilizing Conventional vehicles, Electric Vehicles require charging the batteries, so the chargers for batteries are becoming more and more crucial within the automobile industry. While the current chargers ...
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The proposed patient monitoring system is a substantial progression in healthcare technology. It integrates various sensors and communication modules to provide real-time patient data to caregivers and medical profess...
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A self-decoupling circularly polarized (CP) multi-input multi-output (MIMO) microstrip patch antenna (MPA) array is proposed. The array comprises two identical square microstrip patch antennas (MPAs) and each patch is...
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This paper proposes an iterative learning control problem based on the differential evolution algorithm for optimal control gains. The proposed framework for a nonlinear discrete-time system consists of open-loop ILC ...
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A rapidly developing field of technological advances in computers is text-to-speech synthesis, which is crucial to many different types of interaction between humans and computers platforms. In this study, we've e...
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