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In this paper, we present a pseudo-key analysis approach for cross-validation of language recognition systems before the ground truth (true key) becomes available. A state-of-the-art language recognition system typically employs multiple language recognition classifiers which are fused to form a mixture of experts. The individual classifiers are also called subsystems. To avoid the fused system from being brought down by some outlier classifiers, pseudo keys are designed to cross-examine the integrity of individual classifier candidates. The language recognition experiments are conducted on the NIST 2007 Language Recognition Evaluation (LRE) corpus using the subsystems in the primary submission from the Institute for Infocomm Research (IIR).