A Comparison of Classifiers in Performing Speaker Accent Recognition Using MFCCs

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Open Journal of Statistics

ISSN Print: 2161-718X
ISSN Online: 2161-7198
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"A Comparison of Classifiers in Performing Speaker Accent Recognition Using MFCCs"
written by Zichen Ma, Ernest Fokoué,
published by Open Journal of Statistics, Vol.4 No.4, 2014

has been cited by the following article(s):

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CrossRef

[1]	A Comparative Study of Machine Learning Classifiers for Speaker's Accent Recognition
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[2]	On Exact Bayesian Credible Sets for Classification and Pattern Recognition
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[3]	Dealing with Data Imbalance in Speaker Accent Recognition Using Fuzzy kNN and IQR
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[4]	Efficient cross-validation traversals in feature subset selection
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[5]	US Accent Recognition Using Machine Learning Methods
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[6]	Implementation of Machine Learning-Aided Speech Analysis for Speaker Accent Identification Applied to Audio Forensics
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[7]	MARS: A Hybrid Deep CNN-based Multi-Accent Recognition System for English Language
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[8]	Accent Recognition Using Mel-Frequency Cepstral Coefficients and Convolutional Neural Network
	… Conference on Innovation …, 2021

[9]	Analisis Fitur dan Convolutional Neural Network pada Pengenalan Aksen Ucapan
	EXPLORE, 2021

[10]	O som eo poder
	(Des) troços: revista de pensamento radical, 2021

[11]	Middle eastern and north african english speech corpus (MENAESC): automatic identification of MENA english accents.
	2021

[12]	Overview of Machine Learners in Classifying of Speech Signals
	2020

[13]	Forensic speaker recognition: A new method based on extracting accent and language information from short utterances
	2020

[14]	Accent Classification of the Three Major Nigerian Indigenous Languages Using 1D CNN LSTM Network Model
	2020

[15]	Weighted lens depth: Some applications to supervised classification
	2020

[16]	Speaker Accent Recognition Using Machine Learning Algorithms
	2020

[17]	Identification of the English Accent Spoken in Different Countries by the k-Nearest Neighbor Method
	2020

[18]	Extracting accent information from Urdu speech for forensic speaker recognition
	2019

[19]	Convolutional Neural Networks for Accent Classification
	2019

[20]	Application of convolutional neural network for gender and age group recognition from speech
	2019

[21]	Emotion Recognition in Speech with Deep Learning Architectures
	Artificial Neural Networks in Pattern Recognition, 2016

[22]	Comparing speech and text classification on icnale
	2016

[23]	MFCC-GMM based accent recognition system for Telugu speech signals
	International Journal of Speech Technology, 2015

[24]	Accent Recognition for Noisy Audio Signals
	Serdica Journal of Computing, 2014

[25]	INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING

[1]	Weighted lens depth: Some applications to supervised classification Canadian Journal of Statistics, 2023 DOI:10.1002/cjs.11724

[2]	A Comparative Study of Machine Learning Classifiers for Speaker’s Accent Recognition 2023 IEEE World AI IoT Congress (AIIoT), 2023 DOI:10.1109/AIIoT58121.2023.10174511

[3]	Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks Advances in Digital Crime, Forensics, and Cyber Terrorism, 2022 DOI:10.4018/978-1-6684-4558-7.ch008

[4]	Weighted lens depth: Some applications to supervised classification Canadian Journal of Statistics, 2022 DOI:10.1002/cjs.11724

[5]	Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks Advances in Digital Crime, Forensics, and Cyber Terrorism, 2022 DOI:10.4018/978-1-6684-4558-7.ch008

[6]	Efficient cross-validation traversals in feature subset selection Scientific Reports, 2022 DOI:10.1038/s41598-022-25942-4

[7]	Efficient cross-validation traversals in feature subset selection Scientific Reports, 2022 DOI:10.1038/s41598-022-25942-4

[8]	Advances in Computational Intelligence Techniques Algorithms for Intelligent Systems, 2020 DOI:10.1007/978-981-15-2620-6_1

[9]	Forensic speaker recognition: A new method based on extracting accent and language information from short utterances Forensic Science International: Digital Investigation, 2020 DOI:10.1016/j.fsidi.2020.300982

[10]	Application of convolutional neural network for gender and age group recognition from speech 2019 6th NAFOSTED Conference on Information and Computer Science (NICS), 2019 DOI:10.1109/NICS48868.2019.9023870

[11]	MFCC-GMM based accent recognition system for Telugu speech signals International Journal of Speech Technology, 2016 DOI:10.1007/s10772-015-9328-y

[12]	Artificial Neural Networks in Pattern Recognition Lecture Notes in Computer Science, 2016 DOI:10.1007/978-3-319-46182-3_25

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