Title :
MFCC and vector quantization for Arabic fricatives speech/speaker recognition
Author :
Chelali, Fatma Zohra ; Djeradi, Amar
Author_Institution :
Speech Commun. & signal Process. Lab., Univ. of Sci. & Technol. Houari Boumedienne, El Alia, Algeria
Abstract :
This article develops a speaker-dependent Arabic phonemes recognition system using MFCC analysis and the VQ-LBG algorithm. The system is examined with and without vector quantization in order to analyze the effect of compression in an acoustic parameterization phase. Our experimental results show that vector quantization using a codebook of size 16 achieves good results compared to the system without quantization for a majority of the phonemes studied.
Keywords :
acoustic signal processing; cepstral analysis; natural language processing; speaker recognition; vector quantisation; Arabic fricatives speech-speaker recognition; MFCC analysis; Mel frequency cepstrals coefficients; VQ-LBG algorithm; acoustic parameterization phase; speaker-dependent Arabic phonemes recognition system; vector quantization; Feature extraction; Mel frequency cepstral coefficient; Speaker recognition; Speech; Speech recognition; Vectors; MFCC; VQ; speaker identification; speech recognition;
Conference_Titel :
Multimedia Computing and Systems (ICMCS), 2012 International Conference on
Conference_Location :
Tangier
Print_ISBN :
978-1-4673-1518-0
DOI :
10.1109/ICMCS.2012.6320121
