PCA-based Feature Extraction for Phonotactic Language Recognition

被引：0

作者：

Mikolov, Tomas ^{[1
]}

Plchot, Oldrich ^{[1
]}

Glembek, Ondrej ^{[1
]}

Matejka, Pavel ^{[1
]}

Burget, Lukas ^{[1
]}

Cernocky, Jan Honza ^{[1
]}

机构：

[1] Brno Univ Technol, Speech FIT, CS-61090 Brno, Czech Republic

来源：

ODYSSEY 2010: THE SPEAKER AND LANGUAGE RECOGNITION WORKSHOP | 2010年

关键词：

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

Phonotactic language recognition is one of major techniques used for automatic recognition of spoken languages. We propose a feature extraction technique based on PCA to be used with SVM-based systems. This technique improves speed of the training, in some cases more than 1000 times, allowing systems to be effectively trained on much larger data sets. Speed-up of the test phase can be even greater, which makes the resulting systems much more useful for processing large amounts of data. We report our results on NIST LRE 2009 task.

引用

页码：251 / 255

页数：5

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