Comparative Analysis of Classifiers for Automatic Language Recognition in Spontaneous Speech

被引：1
|
作者：
Simonchik, Konstantin [1 ,2 ]
Novoselov, Sergey [1 ,2 ]
Lavrentyeva, Galina [1 ,2 ]
机构：
[1] ITMO Univ, St Petersburg, Russia
[2] Speech Technol Ctr, Krasutskogo St 4, St Petersburg 196084, Russia
来源：
SPEECH AND COMPUTER | 2016年 / 9811卷
关键词：
Language recognition; i-vectors; SVM; LDA; Naive bayes;
D O I：
10.1007/978-3-319-43958-7_20
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we consider a language identification system based on the state-of-the-art i-vector method. Paper presents a comparative analysis of different methods for the classification in the i-vector space to determine the most efficient for this task. Experimental results show the reliability of the method based on linear discriminant analysis and naive Bayes classifier which is sufficient for usage in practical applications.
引用
收藏
页码：174 / 181
页数：8
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