Speaker Identification Approach Based On Time Domain Extracted Features

被引：0

作者：

Lupu, Eugen ^{[1
]}

Emerich, Simina ^{[1
]}

机构：

[1] Tech Univ Cluj Napoca, Dept Commun, Cluj Napoca, Romania

来源：

PROCEEDINGS ELMAR-2010 | 2010年

关键词：

speaker identification; TESPAR; epoch; SVM; confusion matrix;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents a speaker identification approach based on features extracted by time domain speech analysis. Most features (28) issue from the TESPAR (Time Encoded Signal Processing and Recognition) coding method. The other four features are provided by the time domain analysis of the waveform. The features further employed are: the relative mean square energy, the number of maxima in the energy envelope, the pitch frequency average and the relative number of zero crossings for every utterance. This approach implies low computational requirements for features extraction and provides good recognition rates. For the experiments some classifiers (kNN, Bayes Net, Naive Bayes, RBF and SVM) provided by the WEKA (Waikato Environment for Knowledge Analysis) environment are employed.

引用

页码：355 / 358

页数：4