Title :
Text independent automatic speaker recognition using selforganizing maps
Author :
Mafra, Alexandre Teixeira ; Simões, Marcelo Godoy
Author_Institution :
Escola Politecnica, Sao Paulo Univ., Sao Paulo, Brazil
Abstract :
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.
Keywords :
cepstral analysis; self-organising feature maps; speaker recognition; vector quantisation; MFCC; SOM neural network; VQ; automatic speaker recognition; mel-frequency cepstral coefficient; selforganizing map neural network; speaker identification task; vector quantization error; Artificial neural networks; Data mining; Feature extraction; Frequency; Hidden Markov models; Neural networks; Self organizing feature maps; Speaker recognition; Testing; Vector quantization;
Conference_Titel :
Industry Applications Conference, 2004. 39th IAS Annual Meeting. Conference Record of the 2004 IEEE
Print_ISBN :
0-7803-8486-5
DOI :
10.1109/IAS.2004.1348670
