MFCC and vector quantization for Arabic fricatives speech/speaker recognition

MFCC and vector quantization for Arabic fricatives speech/speaker recognition

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 th...

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Bibliographische Detailangaben
Hauptverfasser: Chelali, Fatma Zohra, Djeradi, A.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Feature extraction
Mel frequency cepstral coefficient
MFCC
speaker identification
Speaker recognition
Speech
Speech recognition
Vectors
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Beschreibung
Zusammenfassung: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.
DOI:10.1109/ICMCS.2012.6320121