Speaker Identification and Verification using Vector Quantization and Mel Frequency Cepstral Coefficients

نویسنده

  • A. Srinivasan
چکیده

In the study of speaker recognition, Mel Frequency Cepstral Coefficient (MFCC) method is the best and most popular which is used to feature extraction. Further vector quantization technique is used to minimize the amount of data to be handled in recent years. In the present study, the Speaker Recognition using Mel Frequency Cepstral coefficients and vector Quantization for the letter “Zha” (in Tamil language) is obtained. The experimental results are analyzed with the help of MATLAB in different situations and it is proved that the results are efficient in the noisy environment.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Speaker Identification Based on Vector Quantization

In this paper a method of text-independent speaker recognition using discrete vector quantization is presented. The identification experiments were performed in a closed set of 599 speakers and two various types of features were tested: cepstral mean subtraction coefficients and mel-frequency cepstral coefficients. The effect of the various codebook size on the speaker identification performanc...

متن کامل

Speaker Recognition Using Gaussian Mixtures Models

Speech signal contains several levels of information. At first it contains information about the spoken message. At second level speech signal also gives information about the speaker identity, his emotional state and so on. The task of speaker recognition can be divided into two parts: speaker identification and speaker verification. Speaker identification is answering the question which one o...

متن کامل

Speaker Verification in Software and Hardware

Combined software and hardware research has been conducted in the Speaker Verification area, where a Speaker Verification application has been developed in JAVA, based on Vector Quantizing, VQ, and Mel Frequency Cepstral Coefficients, MFCC’s. Extended research has been carried out on the Fourier Transform, since it is one of the parts demanding most computational power in the Speaker Verificati...

متن کامل

An Improved Approach for Text-Independent Speaker Recognition

This paper presents new Speaker Identification and Speaker Verification systems based on the use of new feature vectors extracted from the speech signal. The proposed structure combine between the most successful Mel Frequency Cepstral Coefficients and new features which are the Short Time Zero Crossing Rate of the signal. A comparison between speaker recognition systems based on Gaussian mixtu...

متن کامل

Formant and F0 Features for Speaker Verification

In this paper, the feature set of fundamental frequency, formant center frequencies, and formant bandwidths were used in speaker verification experiments using the database distributed by the Speaker Odyssey Workshop. The features were extracted using the Entropic Signal Processing System. The main classifier was a Gaussian Mixture Model system built by MIT Lincoln Laboratory, but tests were al...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011