Mokgonyane, TBSefara, Tshephisho JModipa, TIManamela, MJ2020-10-052020-10-052019-09Mokgonyane, T.B. (et.al.) 2019. Automatic speaker recognition system based on optimised machine learning algorithms. IEEE AFRICON, Accra, Ghana, 25-27 September 2019, 7pp.978-1-7281-3289-1https://dblp.org/db/conf/africon/index.htmlafricon2019.orghttps://ieeexplore.ieee.org/document/9133823DOI: 10.1109/AFRICON46755.2019.9133823http://hdl.handle.net/10204/11592Copyright: 2019 IEEE. This is the accepted version of the published item.Speaker recognition is a technique that automatically identifies a speaker from a recording of their voice. Speaker recognition technologies are taking a new trend due to the progress in artificial intelligence and machine learning and have been widely used in many domains. Continuing research in the field of speaker recognition has now spanned over 50 years. In over half a century, a great deal of progress has been made towards improving the accuracy of the system’s decisions, through the use of more successful machine learning algorithms. This paper presents the development of automatic speaker recognition system based on optimised machine learning algorithms. The algorithms are optimised for better and improved performance. Four classifier models, namely, Support Vector Machines, K-Nearest Neighbors, Random Forest, Logistic Regression, and Artificial Neural Networks are trained and compared. The system resulted with Artificial Neural Networks obtaining the state-ofthe-art accuracy of 96.03% outperforming KNN, SVM, RF and LR classifiers.enSpeaker recognitionSupport vector machinesK-nearest neighborsArtificial neural networksLogistic regressionConference PresentationMokgonyane, T., Sefara, T. J., Modipa, T., & Manamela, M. (2019). Automatic speaker recognition system based on optimised machine learning algorithms. IEEE. http://hdl.handle.net/10204/11592Mokgonyane, TB, Tshephisho J Sefara, TI Modipa, and MJ Manamela. "Automatic speaker recognition system based on optimised machine learning algorithms." (2019): http://hdl.handle.net/10204/11592Mokgonyane T, Sefara TJ, Modipa T, Manamela M, Automatic speaker recognition system based on optimised machine learning algorithms; IEEE; 2019. http://hdl.handle.net/10204/11592 .TY - Conference Presentation AU - Mokgonyane, TB AU - Sefara, Tshephisho J AU - Modipa, TI AU - Manamela, MJ AB - Speaker recognition is a technique that automatically identifies a speaker from a recording of their voice. Speaker recognition technologies are taking a new trend due to the progress in artificial intelligence and machine learning and have been widely used in many domains. Continuing research in the field of speaker recognition has now spanned over 50 years. In over half a century, a great deal of progress has been made towards improving the accuracy of the system’s decisions, through the use of more successful machine learning algorithms. This paper presents the development of automatic speaker recognition system based on optimised machine learning algorithms. The algorithms are optimised for better and improved performance. Four classifier models, namely, Support Vector Machines, K-Nearest Neighbors, Random Forest, Logistic Regression, and Artificial Neural Networks are trained and compared. The system resulted with Artificial Neural Networks obtaining the state-ofthe-art accuracy of 96.03% outperforming KNN, SVM, RF and LR classifiers. DA - 2019-09 DB - ResearchSpace DP - CSIR KW - Speaker recognition KW - Support vector machines KW - K-nearest neighbors KW - Artificial neural networks KW - Logistic regression LK - https://researchspace.csir.co.za PY - 2019 SM - 978-1-7281-3289-1 T1 - Automatic speaker recognition system based on optimised machine learning algorithms TI - Automatic speaker recognition system based on optimised machine learning algorithms UR - http://hdl.handle.net/10204/11592 ER -