Gorgunoglu, S.Ozkaynak, E.Orak, I.M.2024-09-292024-09-2920121308-772Xhttps://hdl.handle.net/20.500.14619/9877Voice is a biometric feature that is used to distinguish or to identify human beings or species. Origin of the existing voice can be determined by analyzing the sound signal. Since voice of the human beings has disparities, it can be used for recognizing people. Various devices or machines are also controlled by voice commands obtained from the words out of the sound signal from one's speeches. In this study, Principal Component Analysis (PCA) algorithm which is mostly used in face recognition system is investigated for voice recognition purposes. PCA algorithm along with Support Vector Machines (SVMs) and K-means algorithms are realized for voice recognition and also their performances are compared. It is shown that PCA algorithm can be used as alternative to the well known voice recognition algorithms © Sila Science.eninfo:eu-repo/semantics/closedAccessK-meansPrincipal component analysis (PCA)Support vector machine (SVM)Voice processingVoice recognitionArticle2-s2.0-84885048156764SPEC .ISS.1N/A75930