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One of the difficulties in Language Recognition is the variability of the speech signal due to speakers and channels. If channel mismatch is too big and when different categories of channels can be identified, one possibility is to build a specific language recognition system for each category and then to fuse them together. This article uses a system selector that takes, for each utterance, the scores of one of the channel-category dependent systems. This selection is guided by a channel detector. We analyze different ways to design such channel detectors: based on cepstral features or on the Factor Analysis channel variability term. The systems are evaluated in the context of NIST's LRE 2009 and run at 1.65% min-Cavg for a subset of 8 languages and at 3.85% min-Cavg for the 23 language protocol.