Text independent automatic speaker recognition using self-organizing maps
A.T. Mafra, Marcelo Godoy Simões · 2004
This work presents one implementation of an automatic speaker recognition system, based on selforganizing map (SOM) neural networks. The voice of each speaker is modeled by a SOM, trained to specialize in the quantization of feature vectors (MFCCs) extracted from his voice. When a test sample is presented, it is quantized by all SpMs, that compete for the speaker: the SOM with smallest quantization error defines the speaker. The system was tested on a speaker identification task over a 14 speaker set, with phrases from three phonetically balanced sets and one variable answer set. The results comprovate the method's efficiency.