Analysis of feature extraction techniques for speech recognition system

Abstract

The audio signal is filtered using a method known as feature extraction technique. In this article, the feature extraction technique for speech recognition and voice classification is analyzed and also centered to comparative analysis of different type of mel-frequency cepstral coefficients (MFCC) feature extraction method. The MFCC technique is used for deduction of noise in voice signal and also used for voice classification and speaker identification. The statistical results of the different MFCC techniques are discussed and finally concluded that the delta-delta MFCC feature extraction technique is better than the other feature extraction techniques.