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This paper describes our Speech-to-Text (STT) system for French, which was developed as part of our efforts in the Quaero program for the 2013 evaluation. Our STT system consists of six subsystems which were created by combining multiple complementary sources of pronunciation modeling including graphemes with various feature front-ends based on deep neural networks and tonal features. Both speaker-independent and speaker adaptively trained versions of the systems were built. The resulting systems were then combined via confusion network combination and crossadaptation. Through progressive advances and system combination we reach a word error rate (WER) of 16.5% on the 2012 Quaero evaluation data.