文章基本信息

标题：Performance Improvement of Speaker Recognition System
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作者：Anand Vardhan Bhalla ; Shailesh Khaparkar ; Mudit Ratana Bhalla 等
期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2012
卷号：2
期号：3
出版社：S.S. Mishra
摘要：Speech processing is emerged as one of the important application area of digital signal processing. Various fields for research in speech processing are speech recognition, speaker recognition, speech synthesis, speech coding etc. Speaker recognition has been an interesting research field for the last many decades, which still have a number of unsolved problems. The objective of automatic speaker recognition is to extract, characterize and recognize the information about speaker identity. A direct analysis and synthesizing the complex voice signal is due to too much information contained in the signal. Therefore the digital signal processes such as Feature Extraction and Feature Matching are introduced to represent the voice signal. Several methods such as Liner Predictive Coding (LPC), Hidden Markov Model (HMM), Artificial Neural Network (ANN) etc are evaluated with a view to identify a straight forward and effective method for speech signal. In this paper, the Mel Frequency Cepstrum Coefficient (MFCC) technique is been explained for designing a speaker recognition system. Some modifications to the existing technique of MFCC for feature extraction are suggested. The purpose of modification in the MFCC based technique generally being used was to improve its performance for making it more robust, accurate and making it faster and computationally efficient. So, that the technique can be considered for real time applications.
关键词：Mel Frequency Cepstral Coefficients; Speech Signal; Vector Quantization; Speaker Recognition System; Windowing