Fantastic 4 system for NIST 2015 Language Recognition Evaluation
نویسندگان
چکیده
This article describes the systems jointly submitted by Institute for Infocomm (IR), the Laboratoire d’Informatique de l’Universit 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 [1] extracted from different types of features. Given the i-vectors, several classifiers are adopted for the language detection task including support vector machines (SVM) [2], multi-class logistic regression (MCLR), Probabilistic Linear Discriminant Analysis (PLDA) [3] and Deep Neural Networks (DNN).
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ورودعنوان ژورنال:
- CoRR
دوره abs/1602.01929 شماره
صفحات -
تاریخ انتشار 2016