Title :
Speaker recognition using Mel frequency Cepstral Coefficients (MFCC) and Vector quantization (VQ) techniques
Author :
Martinez, Jorge ; Perez, Hector ; Escamilla, Enrique ; Suzuki, Masahisa Mabo
Author_Institution :
Nat. Polytech. Inst. (IPN), Mexico City, Mexico
Abstract :
This paper presents a fast and accurate automatic voice recognition algorithm. We use Mel frequency Cepstral Coefficient (MFCC) to extract the features from voice and Vector quantization technique to identify the speaker, this technique is usually used in data compression, it allows to model a probability functions by the distribution of different vectors, the results that we achieve were 100% of precision with a database of 10 speakers.
Keywords :
feature extraction; probability; speaker recognition; vector quantisation; MFCC; Mel frequency cepstral coefficients; automatic voice recognition algorithm; data compression; feature extraction; probability functions; speaker database; speaker identification; speaker recognition; vector quantization techniques; voice quantization technique; Databases; Filter banks; Mel frequency cepstral coefficient; Speaker recognition; Speech; Speech recognition; Vectors; Discrete Fourier Transform; MFCC; Speech processing; Vector Quantization; Voice; speaker recognition;
Conference_Titel :
Electrical Communications and Computers (CONIELECOMP), 2012 22nd International Conference on
Conference_Location :
Cholula, Puebla
Print_ISBN :
978-1-4577-1326-2
DOI :
10.1109/CONIELECOMP.2012.6189918
