文章基本信息

标题：Speaker Identification Using GMM with MFCC
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作者：Tahira Mahboob ; Memoona Khanum ; Malik Sikandar Hayat Khiyal 等
期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2015
卷号：12
期号：2
出版社：IJCSI Press
摘要：Speaker identification comes under the field of digital signal processing. The earliest systems were based on acoustic phonetics built for Automatic Speech Recognition. For recognition part these systems used pattern matching and spectrum analysis. With recent advancement in technology voice recognition has become one of the efficient measure that is used to provide protection to humans computerized and electronic belongings. Voice recognition technology is the most potential technology that will make our daily lives more secure. It is one of the types of biometric that is used to identify and authenticate user on the basis of his/her voice. Voice recognition is divided into two types: text dependent and text independent. Text dependent recognition identifies user against a phrase while text independent recognition identifies the user irrespective of what he is saying. The success in both cases depends upon the various speaker characteristics which differentiate the one speaker from other. This paper targets the implementation of MFCC with GMM techniques in order to identify a speaker.
关键词：Mel frequency Cepstral coefficient (MFCC); Gaussian Mixture Modeling; Expectation Maximization (EM) algorithm; Feature matching; Fast fourier Transform; Discrete fourier Transform; Clustering;window; Melfilter