Abstract
Speaker recognition and speech recognition are both related. As against determining what was said, speaker recognition enables the automatic recognition of who is speaking based on the speaker’s voice’s unique characteristics. This paper presents a simple approach to text dependent speaker identification and is based on the Symlet wavelets for feature extraction. The extracted features are then classified using data mining algorithms. In this study, J48, Naive Bayes and SVM are used for classifying the features.
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