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This paper analyzes Dynamic Time Warping (DTW) and Vector Quantization (V Q) technique for speaker recognition showing performance of each model. Text independent (T I) experiments are realized with V Q and text dependent (T D) experiments are realized with V Q and DTW.

Comparing performance of a speaker recognition system for Dynamic Time Warping and Vector Quantization models