Speaker Identification Using Higher Order Spectral Phase Features and their Effectiveness vis–a–vis Mel-Cepstral Features

2004 ◽  
pp. 614-622 ◽  
Author(s):  
Vinod Chandran ◽  
Daryl Ning ◽  
Sridha Sridharan
Keyword(s):  
Speaker Identification ◽  
Higher Order ◽  
Spectral Phase ◽  
Cepstral Features

scholarly journals Automatic Speaker Identification by Voice Based on Vector Quantization Method

2019 ◽  
Vol 8 (10) ◽  
pp. 2443-2445
Keyword(s):  
Feature Extraction ◽  
Vector Quantization ◽  
Speaker Identification ◽  
Voice Recognition ◽  
Recognition System ◽  
Automatic Identification ◽  
Quantization Method ◽  
Feature Vectors ◽  
Cepstral Features ◽  
Code Book

In this paper, the systems of speaker identification of a text-dependent and independent nature were considered. Feature extraction was performed using chalk-frequency cepstral coefficients (MFCC). The vector quantization method for the automatic identification of a person by voice has been investigated. Using the extracted features, the code book from each speaker was built by clustering the feature vectors. Speakers were modeled using vector quantization (VQ). Using the extracted features, the code book from each speaker was built by clustering the feature vectors. Codebooks of all announcers were collected in the database. From the results, it can be said that vector quantization using cepstral features produces good results for creating a voice recognition system.

Wavelet Packet Based Mel Frequency Cepstral Features for Text Independent Speaker Identification

2013 ◽  
pp. 237-247 ◽  
Author(s):  
Smriti Srivastava ◽  
Saurabh Bhardwaj ◽  
Abhishek Bhandari ◽  
Krit Gupta ◽  
Hitesh Bahl ◽  
...  
Keyword(s):  
Speaker Identification ◽  
Wavelet Packet ◽  
Cepstral Features
Sign in / Sign up

Export Citation Format

Share Document