期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：1
出版社：S&S Publications
摘要：Speech recognition is a natural means of interaction for a human with a smart assistive environment. In order for this interaction to be effective, such a system should attain a high recognition rate even under adverse conditions. In Speech Recognition speech signals are automatically converted into the correspond ing sequence of words in text. When the training and testing conditions are not similar, statistical speech recognition algorithms suffer from severe degradation in recognition accuracy. So we depend on intelligent and recognizable sounds for common commun ications. In this paper, we first give a brief overview of Speech Recognition and then describe some feature extraction and classifier technique. We have compared MFCC, LPC and PLP feature extraction techniques. We efficiently tested the performance of MFC C is more efficient and accurate then LPC and PLP feature extraction technique in voice recognition and thus more suitable for practical applications.
关键词：Feature extraction; feature matching; MFCC; LPC; PLP; ANN; HMM; DTW; Vector Quantization; ; Ga ; ussian Mixture Model
