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arXiv · 1602.01929

Fantastic 4 system for NIST 2015 Language Recognition Evaluation

Kong Aik Lee·Ville Hautamäki·Anthony Larcher·Wei Rao·Hanwu Sun·Trung Hieu Nguyen·Guangsen Wang·Aleksandr Sizov·Ivan Kukanov·Amir Poorjam·Trung Ngo Trong·Xiong Xiao·Cheng-Lin Xu·Hai-Hua Xu·Bin Ma·Haizhou Li·Sylvain Meignier
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Abstract

This article describes the systems jointly submitted by Institute for Infocomm (I$^2$R), the Laboratoire d'Informatique de l'Universit\'e du Maine (LIUM), Nanyang Technology University (NTU) and the University of Eastern Finland (UEF) for 2015 NIST Language Recognition Evaluation (LRE). The submitted system is a fusion of nine sub-systems based on i-vectors extracted from different types of features. Given the i-vectors, several classifiers are adopted for the language detection task including support vector machines (SVM), multi-class logistic regression (MCLR), Probabilistic Linear Discriminant Analysis (PLDA) and Deep Neural Networks (DNN).

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Kong Aik Lee, Ville Hautamäki, Anthony Larcher, Wei Rao, Hanwu Sun, Trung Hieu Nguyen, Guangsen Wang, Aleksandr Sizov, Ivan Kukanov, Amir Poorjam, Trung Ngo Trong, Xiong Xiao, Cheng-Lin Xu, Hai-Hua Xu, Bin Ma, Haizhou Li, Sylvain Meignier. 2016-02-05. Fantastic 4 system for NIST 2015 Language Recognition Evaluation. https://arxiv.org/abs/1602.01929

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