I2R-NUS Submission to Oriental Language Recognition AP16-OL7 Challenge

I2R-NUS Submission to Oriental Language Recognition AP16-OL7 Challenge
Title:
I2R-NUS Submission to Oriental Language Recognition AP16-OL7 Challenge
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Asia-Pacific Signal and Information Processing Association (APSIPA) Regional Conference (2017)
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12 December 2017
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Abstract:
This paper presents a detailed description and analysis of a joint submission of Institute for Infocomm Research (I2R) and National University of Singapore (NUS), which is the top performing system to AP16-OL7 Challenge. The submitted system was a fusion of two sub-systems: the i-vector system and GMM-SVM system, both based on state-of-the-art bottleneck feature. Central to our work presented in this paper is a language-dependent UBM GMM-SVM system and traditional i-vector polynomials expansion with SVM classifier. The FoCal toolkit was used for sub-system fusion. Experimental results show that the proposed approach achieves significant improvement over the baseline system on the development and evaluation sets. Our final submission achieve EER 0.440%, 1.09% and identification rates 98.9%, 97.6% on the development set and evaluation set, respectively.
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