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- W2533703048 abstract "Speaker recognition is a biometric identification method that uses different features of individual's voice for automatically identifying a speaker among a population. Two different features set for text dependent speaker recognition. A comparison is performed between Linear Predictive Coefficients (LPC) and Prosodic Features (F0, F1, F2, and F3) along with Radial Basis Function Network (RBFN) for recognizing a speaker population of 100 speakers. The results conclude that prosodic features performed better than LPC in terms of accuracy, precision and recall." @default.
- W2533703048 created "2016-10-28" @default.
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- W2533703048 date "2014-09-01" @default.
- W2533703048 modified "2023-09-23" @default.
- W2533703048 title "Comparative Analysis of Prosodic Features and Linear Predictive Coefficients for Speaker Recognition Using Machine Learning Technique" @default.
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- W2533703048 doi "https://doi.org/10.1109/icdccom.2014.7024705" @default.
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