GAUSSIAN BACKEND DESIGN FOR OPEN-SET LANGUAGE DETECTION

被引：6

作者：

BenZeghiba, Mohamed Faouzi ^{[1
]}

Gauvain, Jean-Luc ^{[1
]}

Lamel, Lori ^{[1
]}

机构：

[1] LIMSI, CNRS, Spoken Language Proc Grp, F-91403 Orsay, France

来源：

2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS | 2009年

关键词：

Language recognition; Open-set; Phonotactic approach; Gaussian Backend; Adaptation;

D O I：

10.1109/ICASSP.2009.4960592

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This paper proposes a new approach to the challenging open-set language detection task. Most state-of-the-art approaches make use of data sources with several out-of-set languages to model such languages. In the proposed approach, no additional data from out-of-set languages is required, only date from the target languages is used. Experiments are conducted using the LRE-05 and the LRE-07 evaluation data sets with the 30s condition. A C-avg of 4.5% and 3.4% is obtained on these data set, respectively. These results are comparable with other reported results.

引用

页码：4349 / 4352

页数：4

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