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Speech emotion recognition method in educational scene based on machine learning
2022
EAI Endorsed Transactions on Scalable Information Systems
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SVM is used to establish speech emotion recognition classifier, and genetic algorithm is used to determine the optimal parameters. ...
In order to effectively improve the accuracy and anti noise performance of speech emotion recognition in educational scenes, a new method based on machine learning is studied. ...
Speech emotion recognition classifier based on SVM algorithm Support vector machine (SVM) is a machine learning algorithm based on statistical learning theory [18] . ...
doi:10.4108/eai.10-2-2022.173380
fatcat:wil75rzc4bbi3ncx2qp5hefxuy
Wa Language Syllables Classification by Support Vector Machine Based on Genetic Algorithm
2017
DEStech Transactions on Computer Science and Engineering
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In this paper, propose the method to classify Wa syllables by support vector machine (SVM) based on genetic algorithm (GA). Firstly, select all the Wa syllables from the speech corpus recorded. ...
Finally, use the K crossover validation method (K-CV) based on genetic algorithm (GA) to get the best parameter values train SVM. ...
Acknowledgments This work is financially supported by Yunnan Provincial Department of Education Science Research Fund Project (2016YJS078), Yunnan Minzu University Overseas Masters Program (3019901). ...
doi:10.12783/dtcse/aita2017/15997
fatcat:l6c4m3c5tza3jgdpblokdqsawa
Primi Isolated Words Spectrogram Classification by Support Vector Machine Based on Immune Genetic Algorithm
2018
DEStech Transactions on Computer Science and Engineering
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We propose a method for Primi isolated words spectrogram classification by support vector machine based on immune genetic algorithm (SVM-IGA). ...
Compared with the speech signal classification, the spectrogram classification by SVM-IGA is better. ...
vector machine optimized by immune genetic algorithm (IGA-SVM). ...
doi:10.12783/dtcse/aiie2017/18186
fatcat:t7tvg4btvjbnnbp452nobmijau
GA Algorithm Optimizing SVM Multi-Class Kernel Parameters Applied in Arabic Speech Recognition
2017
Indian Journal of Science and Technology
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Objectives: This paper proposes a novel recognition technique (ASR) based on GA optimized SVM multi-class algorithm. ...
Methods/Statistical Analysis: The Kernel parameters of support vector machine are very important problems that have a great influence on the performance of recognition rate. ...
Algorithm Genetic Algorithms (GA) represent a rather rich and interesting family of stochastic optimization algorithms based on the mechanisms of natural selection and genetics. ...
doi:10.17485/ijst/2017/v10i27/114943
fatcat:zprzl2vubvbulot7xcwktgj76a
The Application of Extreme Learning Machine and Support Vector Machine in Speech Endpoint Detection
2016
International Journal of Control and Automation
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In this method, the Extreme Learning Machine (ELM) and Genetic Algorithm ( GA) optimization Support Vector Machine (SVM) is used as the training and recognition model. ...
In this paper, a general voice activity detection (VAD) method based on pattern recognition is proposed, and a specific algorithm of endpoint detection is researched. ...
Acknowledgements The authors would like to thank the financial support of the financial support of Natural Science Foundation of Liaoning 2013024010. ...
doi:10.14257/ijca.2016.9.12.17
fatcat:6chg4vqlr5e4jc52u7hi54m4em
Speaker Recognition using Support Vector Machine
2014
International Journal of Computer Applications
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Speaker recognition is the process of recognizing the speaker based on characteristics such as pitch ,tone in the speech wave.Background noise influences the overall efficiency of speaker recognition system ...
It reduces the dimensionality of the input vector .These MFCCs are used as the speaker features for matching via Support Vector Machine (SVM) method. ...
Optimal hyperplane is completely defined by support vectors.
Fig. 5: A linear support vector machine. ...
doi:10.5120/15178-3379
fatcat:csk44g5wfzgibhvcjw7xzjxmbm
Genetic Analysis with Feature Reduction to Predict the Onset of Parkinson's disease
2020
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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This paper further applies feature reduction techniques using a genetic algorithm for efficient prediction of Parkinson's disease along with machine learning-based approaches. ...
This paper studies the bias of various traditional algorithms on the voice-based data that has various parameters recorded from Parkinson patients and healthy patients. ...
Support Vector Machine and Naïve Bayes classification algorithms predicted with the highest accuracy on Parkinson's speech dataset. ...
doi:10.35940/ijitee.j7337.0891020
fatcat:6rlrl7757vh3fnlmsjeblgelzq
Efficient Approach Multiclass SVM For Vowels Recognition
2011
Conférence Internationale sur l'Informatique et ses Applications
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The proposed paradigm builds a binary tree for multiclass SVM by genetic algorithms with the aim of obtaining optimal partitions for the optimal tree. ...
In the context of phonetic classification by EAMSVM machine, a recognition rate of 57.54%, on the 20 vowels of TIMIT corpus was achieved. ...
Genetic Algorithm for Binary Tree Construction Genetic algorithms (GA) can provide good solutions to many optimization problems. They are based on natural processes of evolution. ...
dblp:conf/ciia/SidaouiS11
fatcat:xklouvlfhndm7grvcfm5ivzp5a
Machine Learning and Pattern Recognition
English
2010
Defence Science Journal
English
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They have used PCA along with support vector regression to estimates the payload and support vector machine for classification of six algorithms. ...
Manju Bala and Agrawal in the paper Statistical measures to determine optimal structure decision treebased one versus one support vector machine have proposed to solve multi-class problems, where optimal ...
doi:10.14429/dsj.60.502
fatcat:yf2m6wthxjal5dusxkzrpujjly
Emotion Recognition and Detection Methods: A Comprehensive Survey
2020
Journal of Artificial Intelligence and Systems
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Overall, the method of Particle Swarm Optimization assisted Biogeography based optimization algorithms with an accuracy of 99.47% on BES dataset gave the best results. Computing. ...
The best results were obtained by using Stationary Wavelet Transform for Facial Emotion Recognition , Particle Swarm Optimization assisted Biogeography based optimization algorithms for emotion recognition ...
Acknowledgement We are very grateful to the editors and reviewers for their suggestions on our paper.
Conflicts of Interest There is no conflict of interest. ...
doi:10.33969/ais.2020.21005
fatcat:3hvis47dcfdubei3zffhbir5fi
Application of Multilayer Perceptron Genetic Algorithm Neural Network in Chinese-English Parallel Corpus Noise Processing
2021
Computational Intelligence and Neuroscience
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The research results show that the neural network recognition method based on genetic algorithm which is given in this paper shows its ability of quickly learning network weights and it is superior to ...
This paper uses neural network as a predictive model and genetic algorithm as an online optimization algorithm to simulate the noise processing of Chinese-English parallel corpus. ...
Acknowledgments is study was supported by Social Science Projects of Guizhou Province, e relationship between family function of nuclear family and children's communicative competence (GZLCLH-2020-278) ...
doi:10.1155/2021/7144635
pmid:34966422
pmcid:PMC8712137
fatcat:afuqhmityffhtorxna2er3dbm4
Artificial Intelligence and Its Applications
2014
Mathematical Problems in Engineering
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Shang propose an economic development prediction method based on the wavelet kernel-based primal twin support vector machine algorithm. ...
In the paper entitled "Nighttime fire/smoke detection system based on a support vector machine, " C.-C. ...
Shang propose an economic development prediction method based on the wavelet kernel-based primal twin support vector machine algorithm. ...
doi:10.1155/2014/840491
fatcat:alknl2oy4faobn5cmcewgdroe4
Optimal Feature Generation with Genetic Algorithms and FLDR in a Restricted-Vocabulary Speech Recognition System
[chapter]
2012
Bio-Inspired Computational Algorithms and Their Applications
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Acknowledgment The authors wish to express their gratitude for financial support of this project to Universidad Politécnica de Aguascalientes.
References ...
www.intechopen.com Optimal Feature Generation with Genetic Algorithms and FLDR in a Restricted-Vocabulary Speech Recognition System 237 The recent apparition of new and robust classifiers such as support ...
.), support vector and other kernel machines, Gaussian mixtures, Bayesian type classifiers, LVQ, and others. ...
doi:10.5772/36135
fatcat:ulwsh7w52baapkzejfhfmc2d7y
Diagnosis of Parkinson's Disorder through Speech Data using Machine Learning Algorithms
2020
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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In this paper, we explore the feature extraction and prediction algorithms used to predict Parkinson's disease and provide a comprehensive comparison of these algorithms ...
Machine learning provides potentially large opportunities for computer-aided identification and diagnosis that could minimize unavoidable health care errors and inherent clinical uncertainty, provide guidance ...
They also used feature sets based on the genetic algorithm (GA) to pick features. R. ...
doi:10.35940/ijitee.c8060.019320
fatcat:liqtwce37fhlvmb3q75ub2lgke
Speech Recognition with Advanced Feature Extraction Methods Using Adaptive Particle Swarm Optimization
2016
International Journal of Intelligent Engineering and Systems
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In this work, from the input speech signal by recognizing the content involves three stages such as the preprocessing, feature extraction and Multi Support Vector Machine (SVM). ...
Nowadays, speech recognition applications are becoming increasingly effective. In the market, different interactive speech aware applications are obtainable. ...
support vector machine (SVM). ...
doi:10.22266/ijies2016.1231.03
fatcat:f6y5ktmqlvgonkiocqenb3pyke
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